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Surv."],"published-print":{"date-parts":[[2026,9,30]]},"abstract":"<jats:p>\n                    Video generation aims to produce temporally coherent sequences of visual frames, representing a pivotal advancement in Artificial Intelligence Generated Content (AIGC). Compared to static image generation, video generation poses unique challenges: it demands not only high-quality individual frames but also strong temporal coherence to ensure consistency throughout the spatiotemporal sequence. Although research addressing spatiotemporal consistency in video generation has increased in recent years, systematic reviews focusing on this core issue remain relatively scarce. To fill this gap, this article views the video generation task as a sequential sampling process from a high-dimensional spatiotemporal distribution, and further discusses spatiotemporal consistency. We provide a systematic review of the latest advancements in the field. The content spans multiple dimensions including generation models, feature representations, generation frameworks, post-processing techniques, training strategies, benchmarks and evaluation metrics, with a particular focus on the mechanisms and effectiveness of various methods in maintaining spatiotemporal consistency. Finally, this article explores future research directions and potential challenges in this field, aiming to provide valuable insights for advancing video generation technology. The project link is\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/Yin-Z-Y\/A-Survey-Spatiotemporal-Consistency-in-Video-Generation\">https:\/\/github.com\/Yin-Z-Y\/A-Survey-Spatiotemporal-Consistency-in-Video-Generation<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1145\/3802588","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T11:08:24Z","timestamp":1776078504000},"page":"1-41","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Survey: Spatiotemporal Consistency in Video Generation"],"prefix":"10.1145","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5280-1280","authenticated-orcid":false,"given":"Zhiyu","family":"Yin","sequence":"first","affiliation":[{"name":"Harbin Institute of Technology","place":["Shenzhen, China"]},{"name":"Central South University","place":["Shenzhen, China"]},{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4346-7618","authenticated-orcid":false,"given":"Kehai","family":"Chen","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology","place":["Shenzhen, China"]},{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7044-0683","authenticated-orcid":false,"given":"Xuefeng","family":"Bai","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6126-2317","authenticated-orcid":false,"given":"Ruili","family":"Jiang","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6286-7529","authenticated-orcid":false,"given":"Juntao","family":"Li","sequence":"additional","affiliation":[{"name":"Soochow University","place":["Suzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3438-739X","authenticated-orcid":false,"given":"Hongdong","family":"Li","sequence":"additional","affiliation":[{"name":"Central South University","place":["Changsha, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4961-7074","authenticated-orcid":false,"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"Central South University","place":["Changsha, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2231-756X","authenticated-orcid":false,"given":"Yang","family":"Xiang","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2316-5478","authenticated-orcid":false,"given":"Jun","family":"Yu","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3895-5510","authenticated-orcid":false,"given":"Min","family":"Zhang","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology","place":["Shenzhen, China"]},{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"key":"e_1_3_3_2_2","unstructured":"Hansi Teng Hongyu Jia Lei Sun Lingzhi Li Maolin Li Mingqiu Tang Shuai Han Tianning Zhang W. Q. Zhang Weifeng Luo et\u00a0al. 2025. Magi-1: Autoregressive video generation at scale. arXiv preprint arXiv:2505.13211 (2025). Retrieved from https:\/\/arxiv.org\/abs\/2505.13211"},{"issue":"2","key":"e_1_3_3_3_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3487891","article-title":"Video generative adversarial networks: A review","volume":"55","author":"Aldausari Nuha","year":"2022","unstructured":"Nuha Aldausari, Arcot Sowmya, Nadine Marcus, and Gelareh Mohammadi. 2022. Video generative adversarial networks: A review. ACM Computing Surveys (CSUR) 55, 2 (2022), 1\u201325. Retrieved from https:\/\/dl.acm.org\/doi\/full\/10.1145\/3487891","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"e_1_3_3_4_2","article-title":"Zigzag diffusion sampling: The path to success is zigzag","author":"Bai Lichen","year":"2024","unstructured":"Lichen Bai, Shitong Shao, Zikai Zhou, Zipeng Qi, Zhiqiang Xu, Haoyi Xiong, and Zeke Xie. 2024. 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Retrieved from https:\/\/arxiv.org\/abs\/2405.04682","journal-title":"arXiv:2405.04682"},{"key":"e_1_3_3_7_2","first-page":"1","volume-title":"SIGGRAPH Asia 2024 Conference Papers","author":"Bar-Tal Omer","year":"2024","unstructured":"Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Guanghui Liu, Amit Raj, et\u00a0al. 2024. Lumiere: A space-time diffusion model for video generation. In SIGGRAPH Asia 2024 Conference Papers. 1\u201311. DOI:https:\/\/dl.acm.org\/doi\/full\/10.1145\/3680528.3687614."},{"key":"e_1_3_3_8_2","unstructured":"Andreas Blattmann Tim Dockhorn Sumith Kulal Daniel Mendelevitch Maciej Kilian Dominik Lorenz Yam Levi Zion English Vikram Voleti Adam Letts et\u00a0al. 2023. Stable video diffusion: Scaling latent video diffusion models to large datasets. arxiv:2311.15127 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2311.15127"},{"key":"e_1_3_3_9_2","first-page":"22563","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Blattmann Andreas","year":"2023","unstructured":"Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis. 2023. Align your latents: High-resolution video synthesis with latent diffusion models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 22563\u201322575. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10203078"},{"key":"e_1_3_3_10_2","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1137\/1.9781611977912.10","volume-title":"Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)","author":"Bringmann Karl","year":"2024","unstructured":"Karl Bringmann, Nick Fischer, Ivor van der Hoog, Evangelos Kipouridis, Tomasz Kociumaka, and Eva Rotenberg. 2024. Dynamic dynamic time warping. In Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). SIAM, 208\u2013242. DOI:https:\/\/epubs.siam.org\/doi\/abs\/10.1137\/1.9781611977912.10."},{"key":"e_1_3_3_11_2","volume-title":"Proceedings of the 41st International Conference on Machine Learning","author":"Bruce Jake","year":"2024","unstructured":"Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, et\u00a0al. 2024. 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Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/hash\/f63f5fbed1a4ef08c857c5f377b5d33a-Abstract-Datasets_and_Benchmarks.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_13_2","first-page":"6221","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Cai Ziqi","year":"2024","unstructured":"Ziqi Cai, Kaiwen Jiang, Shu-Yu Chen, Yu-Kun Lai, Hongbo Fu, Boxin Shi, and Lin Gao. 2024. Real-time 3D-aware portrait video relighting. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 6221\u20136231. Retrieved from https:\/\/www.computer.org\/csdl\/proceedings-article\/cvpr\/2024\/530000g221\/20hNLqKD3KE"},{"key":"e_1_3_3_14_2","article-title":"Gamegen-x: Interactive open-world game video generation","author":"Che Haoxuan","year":"2024","unstructured":"Haoxuan Che, Xuanhua He, Quande Liu, Cheng Jin, and Hao Chen. 2024. 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Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/2aee1c4159e48407d68fe16ae8e6e49e-Abstract-Conference.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_16_2","unstructured":"Guibin Chen Dixuan Lin Jiangping Yang Chunze Lin Junchen Zhu Mingyuan Fan Hao Zhang Sheng Chen Zheng Chen Chengcheng Ma et\u00a0al. 2025. SkyReels-V2: Infinite-length film generative model. arxiv:2504.13074 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2504.13074"},{"key":"e_1_3_3_17_2","unstructured":"Haoxin Chen Menghan Xia Yingqing He Yong Zhang Xiaodong Cun Shaoshu Yang Jinbo Xing Yaofang Liu Qifeng Chen Xintao Wang et\u00a0al. 2023. VideoCrafter1: Open diffusion models for high-quality video generation. arxiv:2310.19512 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2310.19512"},{"key":"e_1_3_3_18_2","article-title":"Od-vae: An omni-dimensional video compressor for improving latent video diffusion model","author":"Chen Liuhan","year":"2024","unstructured":"Liuhan Chen, Zongjian Li, Bin Lin, Bin Zhu, Qian Wang, Shenghai Yuan, Xing Zhou, Xinhua Cheng, and Li Yuan. 2024. Od-vae: An omni-dimensional video compressor for improving latent video diffusion model. arXiv:2409.01199. Retrieved from https:\/\/arxiv.org\/abs\/2409.01199","journal-title":"arXiv:2409.01199"},{"key":"e_1_3_3_19_2","unstructured":"Shoufa Chen Chongjian Ge Yuqi Zhang Yida Zhang Fengda Zhu Hao Yang Hongxiang Hao Hui Wu Zhichao Lai Yifei Hu et\u00a0al. 2025. Goku: Flow based video generative foundation models. arxiv:2502.04896 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2502.04896"},{"key":"e_1_3_3_20_2","unstructured":"Weifeng Chen Yatai Ji Jie Wu Hefeng Wu Pan Xie Jiashi Li Xin Xia Xuefeng Xiao and Liang Lin. 2024. 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Phased one-step adversarial equilibrium for video diffusion models. arxiv:2508.21019 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2508.21019"},{"key":"e_1_3_3_23_2","article-title":"Sora as an AGI world model? A complete survey on text-to-video generation","author":"Cho Joseph","year":"2024","unstructured":"Joseph Cho, Fachrina Dewi Puspitasari, Sheng Zheng, Jingyao Zheng, Lik-Hang Lee, Tae-Ho Kim, Choong Seon Hong, and Chaoning Zhang. 2024. Sora as an AGI world model? A complete survey on text-to-video generation. arXiv:2403.05131. Retrieved from https:\/\/arxiv.org\/abs\/2403.05131","journal-title":"arXiv:2403.05131"},{"key":"e_1_3_3_24_2","unstructured":"Google DeepMind. 2024. Veo. Retrieved from https:\/\/deepmind.google\/models\/veo\/"},{"key":"e_1_3_3_25_2","article-title":"Autoregressive video generation without vector quantization","author":"Deng Haoge","year":"2024","unstructured":"Haoge Deng, Ting Pan, Haiwen Diao, Zhengxiong Luo, Yufeng Cui, Huchuan Lu, Shiguang Shan, Yonggang Qi, and Xinlong Wang. 2024. Autoregressive video generation without vector quantization. arXiv:2412.14169. Retrieved from https:\/\/arxiv.org\/abs\/2412.14169","journal-title":"arXiv:2412.14169"},{"issue":"2","key":"e_1_3_3_26_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3556544","article-title":"Video frame interpolation: A comprehensive survey","volume":"19","author":"Dong Jiong","year":"2023","unstructured":"Jiong Dong, Kaoru Ota, and Mianxiong Dong. 2023. Video frame interpolation: A comprehensive survey. ACM Transactions on Multimedia Computing, Communications and Applications 19, 2s (2023), 1\u201331. Retrieved from https:\/\/dl.acm.org\/doi\/full\/10.1145\/3556544","journal-title":"ACM Transactions on Multimedia Computing, Communications and Applications"},{"key":"e_1_3_3_27_2","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy Alexey","year":"2020","unstructured":"Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et\u00a0al. 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv:2010.11929. Retrieved from https:\/\/arxiv.org\/abs\/2010.11929","journal-title":"arXiv:2010.11929"},{"key":"e_1_3_3_28_2","first-page":"7346","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Esser Patrick","year":"2023","unstructured":"Patrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog, and Anastasis Germanidis. 2023. Structure and content-guided video synthesis with diffusion models. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 7346\u20137356. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10377444"},{"issue":"4","key":"e_1_3_3_29_2","doi-asserted-by":"crossref","first-page":"100152","DOI":"10.1016\/j.tbench.2024.100152","article-title":"AIGCBench: Comprehensive evaluation of image-to-video content generated by AI","volume":"3","author":"Fan Fanda","year":"2023","unstructured":"Fanda Fan, Chunjie Luo, Wanling Gao, and Jianfeng Zhan. 2023. AIGCBench: Comprehensive evaluation of image-to-video content generated by AI. BenchCouncil Transactions on Benchmarks, Standards and Evaluations 3, 4 (2023), 100152. Retrieved from https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2772485924000048","journal-title":"BenchCouncil Transactions on Benchmarks, Standards and Evaluations"},{"key":"e_1_3_3_30_2","article-title":"Tc-bench: Benchmarking temporal compositionality in text-to-video and image-to-video generation","author":"Feng Weixi","year":"2024","unstructured":"Weixi Feng, Jiachen Li, Michael Saxon, Tsu-jui Fu, Wenhu Chen, and William Yang Wang. 2024. Tc-bench: Benchmarking temporal compositionality in text-to-video and image-to-video generation. arXiv:2406.08656. Retrieved from https:\/\/arxiv.org\/abs\/2406.08656","journal-title":"arXiv:2406.08656"},{"key":"e_1_3_3_31_2","first-page":"7277","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Ge Songwei","year":"2024","unstructured":"Songwei Ge, Aniruddha Mahapatra, Gaurav Parmar, Jun-Yan Zhu, and Jia-Bin Huang. 2024. On the content bias in Fr\u00e9chet video distance. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 7277\u20137288. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10655312"},{"key":"e_1_3_3_32_2","first-page":"22930","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Ge Songwei","year":"2023","unstructured":"Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, and Yogesh Balaji. 2023. Preserve your own correlation: A noise prior for video diffusion models. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 22930\u201322941. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10378103"},{"key":"e_1_3_3_33_2","doi-asserted-by":"crossref","unstructured":"Rohit Girdhar Mannat Singh Andrew Brown Quentin Duval Samaneh Azadi Sai Saketh Rambhatla Akbar Shah Xi Yin Devi Parikh and Ishan Misra. 2024. Emu video: Factorizing text-to-video generation by explicit image conditioning. arxiv:2311.10709 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2311.10709","DOI":"10.1007\/978-3-031-73033-7_12"},{"key":"e_1_3_3_34_2","volume-title":"Proceedings of the 12th International Conference on Learning Representations, ICLR 2024","author":"Guo Yuwei","year":"2024","unstructured":"Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, and Bo Dai. 2024. ANIMATEDIFF: Animate your personalized text-to-image diffusion models without specific tuning. In Proceedings of the 12th International Conference on Learning Representations, ICLR 2024."},{"key":"e_1_3_3_35_2","article-title":"Improving autoregressive image generation through coarse-to-fine token prediction","author":"Guo Ziyao","year":"2025","unstructured":"Ziyao Guo, Kaipeng Zhang, and Michael Qizhe Shieh. 2025. Improving autoregressive image generation through coarse-to-fine token prediction. arXiv:2503.16194. Retrieved from https:\/\/arxiv.org\/abs\/2503.16194","journal-title":"arXiv:2503.16194"},{"key":"e_1_3_3_36_2","article-title":"Ltx-video: Realtime video latent diffusion","author":"HaCohen Yoav","year":"2024","unstructured":"Yoav HaCohen, Nisan Chiprut, Benny Brazowski, Daniel Shalem, Dudu Moshe, Eitan Richardson, Eran Levin, Guy Shiran, Nir Zabari, Ori Gordon, et\u00a0al. 2024. Ltx-video: Realtime video latent diffusion. arXiv:2501.00103. Retrieved from https:\/\/arxiv.org\/abs\/2501.00103","journal-title":"arXiv:2501.00103"},{"key":"e_1_3_3_37_2","first-page":"18858","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Han Hui","year":"2025","unstructured":"Hui Han, Siyuan Li, Jiaqi Chen, Yiwen Yuan, Yuling Wu, Yufan Deng, Chak Tou Leong, Hanwen Du, Junchen Fu, Youhua Li, et\u00a0al. 2025. Video-Bench: Human-aligned video generation benchmark. In Proceedings of the Computer Vision and Pattern Recognition Conference. 18858\u201318868. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11094238"},{"key":"e_1_3_3_38_2","first-page":"125","volume-title":"Proceedings of the European Conference on Computer Vision","author":"He Jin-Ting","year":"2025","unstructured":"Jin-Ting He, Fu-Jen Tsai, Jia-Hao Wu, Yan-Tsung Peng, Chung-Chi Tsai, Chia-Wen Lin, and Yen-Yu Lin. 2025. Domain-adaptive video deblurring via test-time blurring. In Proceedings of the European Conference on Computer Vision. Springer, 125\u2013142. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-73404-5_8"},{"key":"e_1_3_3_39_2","article-title":"Latent video diffusion models for high-fidelity long video generation","author":"He Yingqing","year":"2022","unstructured":"Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, and Qifeng Chen. 2022. Latent video diffusion models for high-fidelity long video generation. arXiv:2211.13221. Retrieved from https:\/\/arxiv.org\/abs\/2211.13221","journal-title":"arXiv:2211.13221"},{"key":"e_1_3_3_40_2","article-title":"Imagen video: High definition video generation with diffusion models","author":"Ho Jonathan","year":"2022","unstructured":"Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, et\u00a0al. 2022. Imagen video: High definition video generation with diffusion models. arXiv:2210.02303. Retrieved from https:\/\/arxiv.org\/abs\/2210.02303","journal-title":"arXiv:2210.02303"},{"key":"e_1_3_3_41_2","first-page":"2722","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Ho Jonathan","year":"2019","unstructured":"Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, and Pieter Abbeel. 2019. Flow++: Improving flow-based generative models with variational dequantization and architecture design. In Proceedings of the International Conference on Machine Learning. PMLR, 2722\u20132730. Retrieved from https:\/\/proceedings.mlr.press\/v97\/ho19a"},{"key":"e_1_3_3_42_2","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems 33 (2020), 6840\u20136851. Retrieved from https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/4c5bcfec8584af0d967f1ab10179ca4b-Abstract.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_43_2","article-title":"Cogvideo: Large-scale pretraining for text-to-video generation via transformers","author":"Hong Wenyi","year":"2022","unstructured":"Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang. 2022. Cogvideo: Large-scale pretraining for text-to-video generation via transformers. arXiv:2205.15868. Retrieved from https:\/\/arxiv.org\/abs\/2205.15868","journal-title":"arXiv:2205.15868"},{"key":"e_1_3_3_44_2","article-title":"Gaia-1: A generative world model for autonomous driving","author":"Hu Anthony","year":"2023","unstructured":"Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado. 2023. Gaia-1: A generative world model for autonomous driving. arXiv:2309.17080. Retrieved from https:\/\/arxiv.org\/abs\/2309.17080","journal-title":"arXiv:2309.17080"},{"key":"e_1_3_3_45_2","first-page":"18219","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Hu Yaosi","year":"2022","unstructured":"Yaosi Hu, Chong Luo, and Zhenzhong Chen. 2022. Make it move: Controllable image-to-video generation with text descriptions. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 18219\u201318228. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/9879437"},{"key":"e_1_3_3_46_2","first-page":"478","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Huang Tao","year":"2024","unstructured":"Tao Huang, Guangqi Jiang, Yanjie Ze, and Huazhe Xu. 2024. Diffusion reward: Learning rewards via conditional video diffusion. In Proceedings of the European Conference on Computer Vision. Springer, 478\u2013495. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-72946-1_27"},{"key":"e_1_3_3_47_2","first-page":"21807","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Huang Ziqi","year":"2024","unstructured":"Ziqi Huang, Yinan He, Jiashuo Yu, Fan Zhang, Chenyang Si, Yuming Jiang, Yuanhan Zhang, Tianxing Wu, Qingyang Jin, Nattapol Chanpaisit, et\u00a0al. 2024. Vbench: Comprehensive benchmark suite for video generative models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 21807\u201321818. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10657096"},{"key":"e_1_3_3_48_2","first-page":"624","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Huang Zhewei","year":"2022","unstructured":"Zhewei Huang, Tianyuan Zhang, Wen Heng, Boxin Shi, and Shuchang Zhou. 2022. Real-time intermediate flow estimation for video frame interpolation. In Proceedings of the European Conference on Computer Vision. Springer, 624\u2013642. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-19781-9_36"},{"key":"e_1_3_3_49_2","first-page":"5325","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Ji Pengliang","year":"2024","unstructured":"Pengliang Ji, Chuyang Xiao, Huilin Tai, and Mingxiao Huo. 2024. T2vbench: Benchmarking temporal dynamics for text-to-video generation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 5325\u20135335. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10678444"},{"key":"e_1_3_3_50_2","first-page":"363","volume-title":"Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)","author":"Jiangkuo Wang","year":"2024","unstructured":"Wang Jiangkuo, Zheng Linwei, Chen Kehai, Bai Xuefeng, and Zhang Min. 2024. Chinese vision-language understanding evaluation. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations). 363\u2013373. Retrieved from https:\/\/aclanthology.org\/2024.ccl-3.41\/"},{"key":"e_1_3_3_51_2","first-page":"48955","article-title":"Miradata: A large-scale video dataset with long durations and structured captions","volume":"37","author":"Ju Xuan","year":"2024","unstructured":"Xuan Ju, Yiming Gao, Zhaoyang Zhang, Ziyang Yuan, Xintao Wang, Ailing Zeng, Yu Xiong, Qiang Xu, and Ying Shan. 2024. Miradata: A large-scale video dataset with long durations and structured captions. Advances in Neural Information Processing Systems 37 (2024), 48955\u201348970. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/57f6683e550eb067936c9e9f0bcb8e31-Abstract-Datasets_and_Benchmarks_Track.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_52_2","unstructured":"Xuan Ju Tianyu Wang Yuqian Zhou He Zhang Qing Liu Nanxuan Zhao Zhifei Zhang Yijun Li Yuanhao Cai Shaoteng Liu et\u00a0al. 2025. EditVerse: Unifying image and video editing and generation with in-context learning. arxiv:2509.20360 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2509.20360"},{"key":"e_1_3_3_53_2","unstructured":"Diederik P. Kingma and Max Welling. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013). Retrieved from https:\/\/arxiv.org\/abs\/1312.6114"},{"key":"e_1_3_3_54_2","article-title":"Hunyuanvideo: A systematic framework for large video generative models","author":"Kong Weijie","year":"2024","unstructured":"Weijie Kong, Qi Tian, Zijian Zhang, Rox Min, Zuozhuo Dai, Jin Zhou, Jiangfeng Xiong, Xin Li, Bo Wu, Jianwei Zhang, et\u00a0al. 2024. Hunyuanvideo: A systematic framework for large video generative models. arXiv:2412.03603. Retrieved from https:\/\/arxiv.org\/abs\/2412.03603","journal-title":"arXiv:2412.03603"},{"key":"e_1_3_3_55_2","unstructured":"Dahyeon Kye Changhyun Roh Sukhun Ko Chanho Eom and Jihyong Oh. 2025. AceVFI: A comprehensive survey of advances in video frame interpolation. arxiv:2506.01061 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2506.01061"},{"issue":"1","key":"e_1_3_3_56_2","first-page":"56","article-title":"A comparison study of dynamic time warping\u2019s variants for time series classification","volume":"4","author":"Lahreche Abdelmadjid","year":"2021","unstructured":"Abdelmadjid Lahreche and Bachir Boucheham. 2021. A comparison study of dynamic time warping\u2019s variants for time series classification. International Journal of Informatics and Applied Mathematics 4, 1 (2021), 56\u201371. Retrieved from https:\/\/dergipark.org.tr\/en\/pub\/ijiam\/article\/819482","journal-title":"International Journal of Informatics and Applied Mathematics"},{"key":"e_1_3_3_57_2","first-page":"14143","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Lei Jiarui","year":"2023","unstructured":"Jiarui Lei, Xiaobo Hu, Yue Wang, and Dong Liu. 2023. Pyramidflow: High-resolution defect contrastive localization using pyramid normalizing flow. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 14143\u201314152. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10204306"},{"key":"e_1_3_3_58_2","article-title":"A comprehensive survey on human video generation: Challenges, methods, and insights","author":"Lei Wentao","year":"2024","unstructured":"Wentao Lei, Jinting Wang, Fengji Ma, Guanjie Huang, and Li Liu. 2024. A comprehensive survey on human video generation: Challenges, methods, and insights. arXiv:2407.08428. Retrieved from https:\/\/arxiv.org\/abs\/2407.08428","journal-title":"arXiv:2407.08428"},{"key":"e_1_3_3_59_2","article-title":"A survey on long video generation: Challenges, methods, and prospects","author":"Li Chengxuan","year":"2024","unstructured":"Chengxuan Li, Di Huang, Zeyu Lu, Yang Xiao, Qingqi Pei, and Lei Bai. 2024. A survey on long video generation: Challenges, methods, and prospects. arXiv:2403.16407. Retrieved from https:\/\/arxiv.org\/abs\/2403.16407","journal-title":"arXiv:2403.16407"},{"key":"e_1_3_3_60_2","first-page":"19730","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Li Junnan","year":"2023","unstructured":"Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023. Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In Proceedings of the International Conference on Machine Learning. PMLR, 19730\u201319742. Retrieved from https:\/\/dl.acm.org\/doi\/abs\/10.5555\/3618408.3619222"},{"key":"e_1_3_3_61_2","article-title":"Videogen: A reference-guided latent diffusion approach for high definition text-to-video generation","author":"Li Xin","year":"2023","unstructured":"Xin Li, Wenqing Chu, Ye Wu, Weihang Yuan, Fanglong Liu, Qi Zhang, Fu Li, Haocheng Feng, Errui Ding, and Jingdong Wang. 2023. Videogen: A reference-guided latent diffusion approach for high definition text-to-video generation. arXiv:2309.00398. Retrieved from https:\/\/arxiv.org\/abs\/2309.00398","journal-title":"arXiv:2309.00398"},{"key":"e_1_3_3_62_2","article-title":"DiCoDe: Diffusion-compressed deep tokens for autoregressive video generation with language models","author":"Li Yizhuo","year":"2024","unstructured":"Yizhuo Li, Yuying Ge, Yixiao Ge, Ping Luo, and Ying Shan. 2024. DiCoDe: Diffusion-compressed deep tokens for autoregressive video generation with language models. arXiv:2412.04446. Retrieved from https:\/\/arxiv.org\/abs\/2412.04446","journal-title":"arXiv:2412.04446"},{"key":"e_1_3_3_63_2","first-page":"17778","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Li Zongjian","year":"2025","unstructured":"Zongjian Li, Bin Lin, Yang Ye, Liuhan Chen, Xinhua Cheng, Shenghai Yuan, and Li Yuan. 2025. WF-VAE: Enhancing video VAE by wavelet-driven energy flow for latent video diffusion model. In Proceedings of the Computer Vision and Pattern Recognition Conference. 17778\u201317788. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11093251"},{"key":"e_1_3_3_64_2","first-page":"17789","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Li Zhuoling","year":"2025","unstructured":"Zhuoling Li, Hossein Rahmani, Qiuhong Ke, and Jun Liu. 2025. LongDiff: Training-free long video generation in one go. In Proceedings of the Computer Vision and Pattern Recognition Conference. 17789\u201317798. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11092527"},{"key":"e_1_3_3_65_2","doi-asserted-by":"crossref","first-page":"109790","DOI":"10.52202\/079017-3483","article-title":"Evaluation of text-to-video generation models: A dynamics perspective","volume":"37","author":"Liao Mingxiang","year":"2024","unstructured":"Mingxiang Liao, Qixiang Ye, Wangmeng Zuo, Fang Wan, Tianyu Wang, Yuzhong Zhao, Jingdong Wang, Xinyu Zhang, et\u00a0al. 2024. Evaluation of text-to-video generation models: A dynamics perspective. Advances in Neural Information Processing Systems 37 (2024), 109790\u2013109816. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/c6483c8a68083af3383f91ee0dc6db95-Abstract-Conference.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_66_2","doi-asserted-by":"crossref","first-page":"5971","DOI":"10.18653\/v1\/2024.emnlp-main.342","volume-title":"Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing","author":"Lin Bin","year":"2024","unstructured":"Bin Lin, Yang Ye, Bin Zhu, Jiaxi Cui, Munan Ning, Peng Jin, and Li Yuan. 2024. Video-LLaVA: Learning united visual representation by alignment before projection. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 5971\u20135984. Retrieved from https:\/\/aclanthology.org\/2024.emnlp-main.342\/"},{"key":"e_1_3_3_67_2","article-title":"VideoDirectorGPT: Consistent multi-scene video generation via LLM-guided planning","author":"Lin Han","year":"2023","unstructured":"Han Lin, Abhay Zala, Jaemin Cho, and Mohit Bansal. 2023. VideoDirectorGPT: Consistent multi-scene video generation via LLM-guided planning. arXiv:2309.15091. Retrieved from https:\/\/arxiv.org\/abs\/2309.15091","journal-title":"arXiv:2309.15091"},{"key":"e_1_3_3_68_2","first-page":"13334","volume-title":"Proceedings of the 39th International Conference on Machine Learning","volume":"162","author":"Lin Jing","year":"2022","unstructured":"Jing Lin, Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Youliang Yan, Xueyi Zou, Henghui Ding, Yulun Zhang, Radu Timofte, and Luc Van Gool. 2022. Flow-guided sparse transformer for video deblurring. In Proceedings of the 39th International Conference on Machine Learning, Vol. 162. PMLR, 13334\u201313343. Retrieved from https:\/\/www.research-collection.ethz.ch\/items\/487b0269-42b8-4e77-a80a-01cccb9a300a"},{"key":"e_1_3_3_69_2","article-title":"Exploring the evolution of physics cognition in video generation: A survey","author":"Lin Minghui","year":"2025","unstructured":"Minghui Lin, Xiang Wang, Yishan Wang, Shu Wang, Fengqi Dai, Pengxiang Ding, Cunxiang Wang, Zhengrong Zuo, Nong Sang, Siteng Huang, et\u00a0al. 2025. Exploring the evolution of physics cognition in video generation: A survey. arXiv:2503.21765. Retrieved from https:\/\/arxiv.org\/abs\/2503.21765","journal-title":"arXiv:2503.21765"},{"key":"e_1_3_3_70_2","article-title":"Reasoning physical video generation with diffusion timestep tokens via reinforcement learning","author":"Lin Wang","year":"2025","unstructured":"Wang Lin, Liyu Jia, Wentao Hu, Kaihang Pan, Zhongqi Yue, Wei Zhao, Jingyuan Chen, Fei Wu, and Hanwang Zhang. 2025. Reasoning physical video generation with diffusion timestep tokens via reinforcement learning. arXiv:2504.15932. Retrieved from https:\/\/arxiv.org\/abs\/2504.15932","journal-title":"arXiv:2504.15932"},{"key":"e_1_3_3_71_2","article-title":"VMBench: A benchmark for perception-aligned video motion generation","author":"Ling Xinran","year":"2025","unstructured":"Xinran Ling, Chen Zhu, Meiqi Wu, Hangyu Li, Xiaokun Feng, Cundian Yang, Aiming Hao, Jiashu Zhu, Jiahong Wu, and Xiangxiang Chu. 2025. VMBench: A benchmark for perception-aligned video motion generation. arXiv:2503.10076. Retrieved from https:\/\/arxiv.org\/abs\/2503.10076","journal-title":"arXiv:2503.10076"},{"key":"e_1_3_3_72_2","unstructured":"Yaron Lipman Ricky T. Q. Chen Heli Ben-Hamu Maximilian Nickel and Matthew Le. 2023. Flow matching for generative modeling. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_3_73_2","article-title":"Mardini: Masked autoregressive diffusion for video generation at scale","author":"Liu Haozhe","year":"2024","unstructured":"Haozhe Liu, Shikun Liu, Zijian Zhou, Mengmeng Xu, Yanping Xie, Xiao Han, Juan C. P\u00e9rez, Ding Liu, Kumara Kahatapitiya, Menglin Jia, et\u00a0al. 2024. Mardini: Masked autoregressive diffusion for video generation at scale. arXiv:2410.20280. Retrieved from https:\/\/arxiv.org\/abs\/2410.20280","journal-title":"arXiv:2410.20280"},{"key":"e_1_3_3_74_2","first-page":"800","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Liu Shuaicheng","year":"2016","unstructured":"Shuaicheng Liu, Ping Tan, Lu Yuan, Jian Sun, and Bing Zeng. 2016. Meshflow: Minimum latency online video stabilization. In Proceedings of the European Conference on Computer Vision. Springer, 800\u2013815. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-319-46466-4_48"},{"key":"e_1_3_3_75_2","article-title":"A survey of AI-generated video evaluation","author":"Liu Xiao","year":"2024","unstructured":"Xiao Liu, Xinhao Xiang, Zizhong Li, Yongheng Wang, Zhuoheng Li, Zhuosheng Liu, Weidi Zhang, Weiqi Ye, and Jiawei Zhang. 2024. A survey of AI-generated video evaluation. arXiv:2410.19884. Retrieved from https:\/\/arxiv.org\/abs\/2410.19884","journal-title":"arXiv:2410.19884"},{"key":"e_1_3_3_76_2","first-page":"22139","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Liu Yaofang","year":"2024","unstructured":"Yaofang Liu, Xiaodong Cun, Xuebo Liu, Xintao Wang, Yong Zhang, Haoxin Chen, Yang Liu, Tieyong Zeng, Raymond Chan, and Ying Shan. 2024. Evalcrafter: Benchmarking and evaluating large video generation models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 22139\u201322149. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10657882"},{"key":"e_1_3_3_77_2","article-title":"Sora: A review on background, technology, limitations, and opportunities of large vision models","author":"Liu Yixin","year":"2024","unstructured":"Yixin Liu, Kai Zhang, Yuan Li, Zhiling Yan, Chujie Gao, Ruoxi Chen, Zhengqing Yuan, Yue Huang, Hanchi Sun, Jianfeng Gao, et\u00a0al. 2024. Sora: A review on background, technology, limitations, and opportunities of large vision models. arXiv:2402.17177. Retrieved from https:\/\/arxiv.org\/abs\/2402.17177","journal-title":"arXiv:2402.17177"},{"key":"e_1_3_3_78_2","article-title":"CODA: Repurposing continuous VAEs for discrete tokenization","author":"Liu Zeyu","year":"2025","unstructured":"Zeyu Liu, Zanlin Ni, Yeguo Hua, Xin Deng, Xiao Ma, Cheng Zhong, and Gao Huang. 2025. CODA: Repurposing continuous VAEs for discrete tokenization. arXiv:2503.17760. Retrieved from https:\/\/arxiv.org\/abs\/2503.17760","journal-title":"arXiv:2503.17760"},{"key":"e_1_3_3_79_2","article-title":"Information constraints on auto-encoding variational bayes","volume":"31","author":"Lopez Romain","year":"2018","unstructured":"Romain Lopez, Jeffrey Regier, Michael I. Jordan, and Nir Yosef. 2018. Information constraints on auto-encoding variational bayes. Advances in Neural Information Processing Systems 31 (2018). Retrieved from https:\/\/proceedings.neurips.cc\/paper\/2018\/hash\/9a96a2c73c0d477ff2a6da3bf538f4f4-Abstract.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_80_2","first-page":"131434","article-title":"Freelong: Training-free long video generation with spectralblend temporal attention","volume":"37","author":"Lu Yu","year":"2024","unstructured":"Yu Lu, Yuanzhi Liang, Linchao Zhu, and Yi Yang. 2024. Freelong: Training-free long video generation with spectralblend temporal attention. Advances in Neural Information Processing Systems 37 (2024), 131434\u2013131455. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/ed67dff7cb96e7e86c4d91c0d5db49bb-Abstract-Conference.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_81_2","article-title":"Videofusion: Decomposed diffusion models for high-quality video generation","author":"Luo Zhengxiong","year":"2023","unstructured":"Zhengxiong Luo, Dayou Chen, Yingya Zhang, Yan Huang, Liang Wang, Yujun Shen, Deli Zhao, Jingren Zhou, and Tieniu Tan. 2023. Videofusion: Decomposed diffusion models for high-quality video generation. arXiv:2303.08320. Retrieved from https:\/\/arxiv.org\/abs\/2303.08320","journal-title":"arXiv:2303.08320"},{"key":"e_1_3_3_82_2","unstructured":"Zhengyao Lv Chenyang Si Junhao Song Zhenyu Yang Yu Qiao Ziwei Liu and Kwan-Yee K. Wong. 2025. FasterCache: Training-free video diffusion model acceleration with high quality. In The Thirteenth International Conference on Learning Representations."},{"issue":"11","key":"e_1_3_3_83_2","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1007\/s10462-025-11331-6","article-title":"Video diffusion generation: Comprehensive review and open problems","volume":"58","author":"Ma Wenping","year":"2025","unstructured":"Wenping Ma, Xiaoting Yang, Licheng Jiao, Lingling Li, Xu Liu, Fang Liu, Puhua Chen, Yuting Yang, Mengru Ma, Long Sun, et\u00a0al. 2025. Video diffusion generation: Comprehensive review and open problems. Artificial Intelligence Review 58, 11 (2025), 338. Retrieved from https:\/\/link.springer.com\/article\/10.1007\/s10462-025-11331-6","journal-title":"Artificial Intelligence Review"},{"key":"e_1_3_3_84_2","unstructured":"Yue Ma Kunyu Feng Zhongyuan Hu Xinyu Wang Yucheng Wang Mingzhe Zheng Xuanhua He Chenyang Zhu Hongyu Liu Yingqing He et\u00a0al. 2025. Controllable video generation: A survey. arxiv:2507.16869 [cs.GR]. Retrieved from https:\/\/arxiv.org\/abs\/2507.16869"},{"key":"e_1_3_3_85_2","article-title":"Video diffusion models: A survey","author":"Melnik Andrew","year":"2024","unstructured":"Andrew Melnik, Michal Ljubljanac, Cong Lu, Qi Yan, Weiming Ren, and Helge Ritter. 2024. Video diffusion models: A survey. arXiv:2405.03150. Retrieved from https:\/\/arxiv.org\/abs\/2405.03150","journal-title":"arXiv:2405.03150"},{"key":"e_1_3_3_86_2","first-page":"18444","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Ni Haomiao","year":"2023","unstructured":"Haomiao Ni, Changhao Shi, Kai Li, Sharon X. Huang, and Martin Renqiang Min. 2023. Conditional image-to-video generation with latent flow diffusion models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 18444\u201318455. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10204290"},{"key":"e_1_3_3_87_2","first-page":"8162","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Nichol Alexander Quinn","year":"2021","unstructured":"Alexander Quinn Nichol and Prafulla Dhariwal. 2021. Improved denoising diffusion probabilistic models. In Proceedings of the International Conference on Machine Learning. PMLR, 8162\u20138171. Retrieved from https:\/\/proceedings.mlr.press\/v139\/nichol21a.html"},{"key":"e_1_3_3_88_2","first-page":"1701","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Niklaus Simon","year":"2018","unstructured":"Simon Niklaus and Feng Liu. 2018. Context-aware synthesis for video frame interpolation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1701\u20131710. Retrieved from https:\/\/www.computer.org\/csdl\/proceedings-article\/cvpr\/2018\/642000b701\/17D45VTRoC0"},{"key":"e_1_3_3_89_2","unstructured":"OpenAI. 2024. Sora. Retrieved fromhttps:\/\/openai.com\/sora\/"},{"key":"e_1_3_3_90_2","unstructured":"OpenAI. 2024. Video generation models as world simulators. https:\/\/openai.com\/index\/video-generation-models-as-world-simulators\/ (2024)."},{"key":"e_1_3_3_91_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2019.2957987"},{"key":"e_1_3_3_92_2","first-page":"26136","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Pan Kaihang","year":"2025","unstructured":"Kaihang Pan, Wang Lin, Zhongqi Yue, Tenglong Ao, Liyu Jia, Wei Zhao, Juncheng Li, Siliang Tang, and Hanwang Zhang. 2025. Generative multimodal pretraining with discrete diffusion timestep tokens. In Proceedings of the Computer Vision and Pattern Recognition Conference. 26136\u201326146. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11094468"},{"key":"e_1_3_3_93_2","first-page":"4195","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Peebles William","year":"2023","unstructured":"William Peebles and Saining Xie. 2023. Scalable diffusion models with transformers. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 4195\u20134205. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10377858"},{"key":"e_1_3_3_94_2","article-title":"Open-sora 2.0: Training a commercial-level video generation model in 200 k","author":"Peng Xiangyu","year":"2025","unstructured":"Xiangyu Peng, Zangwei Zheng, Chenhui Shen, Tom Young, Xinying Guo, Binluo Wang, Hang Xu, Hongxin Liu, Mingyan Jiang, Wenjun Li, et\u00a0al. 2025. Open-sora 2.0: Training a commercial-level video generation model in 200 k. arXiv:2503.09642. Retrieved from https:\/\/arxiv.org\/abs\/2503.09642","journal-title":"arXiv:2503.09642"},{"key":"e_1_3_3_95_2","article-title":"Movie gen: A cast of media foundation models","author":"Polyak Adam","year":"2024","unstructured":"Adam Polyak, Amit Zohar, Andrew Brown, Andros Tjandra, Animesh Sinha, Ann Lee, Apoorv Vyas, Bowen Shi, Chih-Yao Ma, Ching-Yao Chuang, et\u00a0al. 2024. Movie gen: A cast of media foundation models. arXiv:2410.13720. Retrieved from https:\/\/arxiv.org\/abs\/2410.13720","journal-title":"arXiv:2410.13720"},{"key":"e_1_3_3_96_2","article-title":"Sora as a world model? A complete survey on text-to-video generation","author":"Puspitasari Fachrina Dewi","year":"2024","unstructured":"Fachrina Dewi Puspitasari, Chaoning Zhang, Joseph Cho, Adnan Haider, Noor Ul Eman, Omer Amin, Alexis Mankowski, Muhammad Umair, Jingyao Zheng, Sheng Zheng, et\u00a0al. 2024. Sora as a world model? A complete survey on text-to-video generation. arXiv:2403.05131. Retrieved from https:\/\/arxiv.org\/abs\/2403.05131","journal-title":"arXiv:2403.05131"},{"key":"e_1_3_3_97_2","first-page":"15932","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Qi Chenyang","year":"2023","unstructured":"Chenyang Qi, Xiaodong Cun, Yong Zhang, Chenyang Lei, Xintao Wang, Ying Shan, and Qifeng Chen. 2023. Fatezero: Fusing attentions for zero-shot text-based video editing. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 15932\u201315942. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10378281"},{"key":"e_1_3_3_98_2","article-title":"xGen-VideoSyn-1: High-fidelity text-to-video synthesis with compressed representations","author":"Qin Can","year":"2024","unstructured":"Can Qin, Congying Xia, Krithika Ramakrishnan, Michael Ryoo, Lifu Tu, Yihao Feng, Manli Shu, Honglu Zhou, Anas Awadalla, Jun Wang, et\u00a0al. 2024. xGen-VideoSyn-1: High-fidelity text-to-video synthesis with compressed representations. arXiv:2408.12590. Retrieved from https:\/\/arxiv.org\/abs\/2408.12590","journal-title":"arXiv:2408.12590"},{"key":"e_1_3_3_99_2","first-page":"6635","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Qing Zhiwu","year":"2024","unstructured":"Zhiwu Qing, Shiwei Zhang, Jiayu Wang, Xiang Wang, Yujie Wei, Yingya Zhang, Changxin Gao, and Nong Sang. 2024. Hierarchical spatio-temporal decoupling for text-to-video generation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 6635\u20136645. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10656893\/"},{"key":"e_1_3_3_100_2","unstructured":"Haonan Qiu Menghan Xia Yong Zhang Yingqing He Xintao Wang Ying Shan and Ziwei Liu. 2024. FreeNoise: Tuning-free longer video diffusion via noise rescheduling. In The Twelfth International Conference on Learning Representations."},{"key":"e_1_3_3_101_2","article-title":"MOVi: Training-free text-conditioned multi-object video generation","author":"Rahman Aimon","year":"2025","unstructured":"Aimon Rahman, Jiang Liu, Ze Wang, Ximeng Sun, Jialian Wu, Xiaodong Yu, Yusheng Su, Vishal M. Patel, Zicheng Liu, and Emad Barsoum. 2025. MOVi: Training-free text-conditioned multi-object video generation. arXiv:2505.22980. Retrieved from https:\/\/arxiv.org\/abs\/2505.22980","journal-title":"arXiv:2505.22980"},{"key":"e_1_3_3_102_2","first-page":"421","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Rao Chen","year":"2024","unstructured":"Chen Rao, Guangyuan Li, Zehua Lan, Jiakai Sun, Junsheng Luan, Wei Xing, Lei Zhao, Huaizhong Lin, Jianfeng Dong, and Dalong Zhang. 2024. Rethinking video deblurring with wavelet-aware dynamic transformer and diffusion model. In Proceedings of the European Conference on Computer Vision. Springer, 421\u2013437. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-72995-9_24"},{"key":"e_1_3_3_103_2","article-title":"Next block prediction: Video generation via semi-auto-regressive modeling","author":"Ren Shuhuai","year":"2025","unstructured":"Shuhuai Ren, Shuming Ma, Xu Sun, and Furu Wei. 2025. Next block prediction: Video generation via semi-auto-regressive modeling. arXiv:2502.07737. Retrieved from https:\/\/arxiv.org\/abs\/2502.07737","journal-title":"arXiv:2502.07737"},{"key":"e_1_3_3_104_2","unstructured":"Zhongwei Ren Yunchao Wei Xun Guo Yao Zhao Bingyi Kang Jiashi Feng and Xiaojie Jin. 2025. VideoWorld: Exploring knowledge learning from unlabeled videos. arxiv:2501.09781 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2501.09781"},{"key":"e_1_3_3_105_2","unstructured":"Runway. 2023. Gen-1: The Next Step Forward for Generative AI. Retrieved from https:\/\/runwayml.com\/research\/gen-1"},{"key":"e_1_3_3_106_2","unstructured":"Runway. 2023. Gen-2: Generate novel videos with text images or video clips. Retrieved from https:\/\/runwayml.com\/research\/gen-2"},{"key":"e_1_3_3_107_2","unstructured":"Runway. 2024. Introducing Gen-3 Alpha: A New Frontier for Video Generation. Retrieved from https:\/\/runwayml.com\/research\/introducing-gen-3-alpha"},{"key":"e_1_3_3_108_2","article-title":"MagicDistillation: Weak-to-strong video distillation for large-scale few-step synthesis","author":"Shao Shitong","year":"2025","unstructured":"Shitong Shao, Hongwei Yi, Hanzhong Guo, Tian Ye, Daquan Zhou, Michael Lingelbach, Zhiqiang Xu, and Zeke Xie. 2025. MagicDistillation: Weak-to-strong video distillation for large-scale few-step synthesis. arXiv:2503.13319. Retrieved from https:\/\/arxiv.org\/abs\/2503.13319","journal-title":"arXiv:2503.13319"},{"key":"e_1_3_3_109_2","first-page":"1250","volume-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","author":"Shi Zhenmei","year":"2022","unstructured":"Zhenmei Shi, Fuhao Shi, Wei-Sheng Lai, Chia-Kai Liang, and Yingyu Liang. 2022. Deep online fused video stabilization. In Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision. 1250\u20131258. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/9706695"},{"key":"e_1_3_3_110_2","article-title":"Make-a-video: Text-to-video generation without text-video data","author":"Singer Uriel","year":"2022","unstructured":"Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, et\u00a0al. 2022. Make-a-video: Text-to-video generation without text-video data. arXiv:2209.14792. Retrieved from https:\/\/arxiv.org\/abs\/2209.14792","journal-title":"arXiv:2209.14792"},{"key":"e_1_3_3_111_2","first-page":"32","volume-title":"Proceedings of the 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC)","author":"Singh Aditi","year":"2023","unstructured":"Aditi Singh. 2023. A survey of AI text-to-image and AI text-to-video generators. In Proceedings of the 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC). IEEE, 32\u201336. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10303174\/"},{"key":"e_1_3_3_112_2","first-page":"3626","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Skorokhodov Ivan","year":"2022","unstructured":"Ivan Skorokhodov, Sergey Tulyakov, and Mohamed Elhoseiny. 2022. Stylegan-v: A continuous video generator with the price, image quality and perks of stylegan2. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 3626\u20133636. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/9878738"},{"key":"e_1_3_3_113_2","first-page":"8406","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Sun Kaiyue","year":"2025","unstructured":"Kaiyue Sun, Kaiyi Huang, Xian Liu, Yue Wu, Zihan Xu, Zhenguo Li, and Xihui Liu. 2025. T2v-compbench: A comprehensive benchmark for compositional text-to-video generation. In Proceedings of the Computer Vision and Pattern Recognition Conference. 8406\u20138416. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11092317"},{"key":"e_1_3_3_114_2","article-title":"From Sora what we can see: A survey of text-to-video generation","author":"Sun Rui","year":"2024","unstructured":"Rui Sun, Yumin Zhang, Tejal Shah, Jiahao Sun, Shuoying Zhang, Wenqi Li, Haoran Duan, Bo Wei, and Rajiv Ranjan. 2024. From Sora what we can see: A survey of text-to-video generation. arXiv:2405.10674. Retrieved from https:\/\/arxiv.org\/abs\/2405.10674","journal-title":"arXiv:2405.10674"},{"key":"e_1_3_3_115_2","article-title":"MotionAura: Generating high-quality and motion consistent videos using discrete diffusion","author":"Susladkar Onkar","year":"2024","unstructured":"Onkar Susladkar, Jishu Sen Gupta, Chirag Sehgal, Sparsh Mittal, and Rekha Singhal. 2024. MotionAura: Generating high-quality and motion consistent videos using discrete diffusion. arXiv:2410.07659. Retrieved from https:\/\/arxiv.org\/abs\/2410.07659","journal-title":"arXiv:2410.07659"},{"key":"e_1_3_3_116_2","article-title":"SweetTokenizer: Semantic-aware spatial-temporal tokenizer for compact visual discretization","author":"Tan Zhentao","year":"2024","unstructured":"Zhentao Tan, Ben Xue, Jian Jia, Junhao Wang, Wencai Ye, Shaoyun Shi, Mingjie Sun, Wenjin Wu, Quan Chen, and Peng Jiang. 2024. SweetTokenizer: Semantic-aware spatial-temporal tokenizer for compact visual discretization. arXiv:2412.10443. Retrieved from https:\/\/arxiv.org\/abs\/2412.10443","journal-title":"arXiv:2412.10443"},{"key":"e_1_3_3_117_2","unstructured":"Junshu Tang Jiacheng Liu Jiaqi Li Longhuang Wu Haoyu Yang Penghao Zhao Siruis Gong Xiang Yuan Shuai Shao and Qinglin Lu. 2025. Hunyuan-GameCraft-2: Instruction-following interactive game world model. arxiv:2511.23429 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2511.23429"},{"key":"e_1_3_3_118_2","unstructured":"CreateAI Team. 2024. Ruyi-Mini-7B. Retrieved from https:\/\/github.com\/IamCreateAI\/Ruyi-Models."},{"key":"e_1_3_3_119_2","first-page":"402","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Teed Zachary","year":"2020","unstructured":"Zachary Teed and Jia Deng. 2020. Raft: Recurrent all-pairs field transforms for optical flow. In Proceedings of the European Conference on Computer Vision. Springer, 402\u2013419. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-030-58536-5_24"},{"key":"e_1_3_3_120_2","first-page":"10078","article-title":"Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training","volume":"35","author":"Tong Zhan","year":"2022","unstructured":"Zhan Tong, Yibing Song, Jue Wang, and Limin Wang. 2022. Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training. Advances in Neural Information Processing Systems 35 (2022), 10078\u201310093. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2022\/hash\/416f9cb3276121c42eebb86352a4354a-Abstract-Conference.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_121_2","first-page":"4489","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Tran Du","year":"2015","unstructured":"Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri. 2015. Learning spatiotemporal features with 3D convolutional networks. In Proceedings of the IEEE International Conference on Computer Vision. 4489\u20134497. Retrieved from https:\/\/www.computer.org\/csdl\/proceedings-article\/iccv\/2015\/8391e489\/12OmNAPSMpP"},{"key":"e_1_3_3_122_2","first-page":"1526","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Tulyakov Sergey","year":"2018","unstructured":"Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz. 2018. Mocogan: Decomposing motion and content for video generation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1526\u20131535. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/8578263"},{"key":"e_1_3_3_123_2","article-title":"Attention is all you need","volume":"31","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in Neural Information Processing Systems 31 (2017). Retrieved from https:\/\/proceedings.neurips.cc\/paper\/2017\/hash\/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_124_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Villegas Ruben","year":"2022","unstructured":"Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, and Dumitru Erhan. 2022. Phenaki: Variable length video generation from open domain textual descriptions. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_3_125_2","first-page":"22532","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Wallace Bram","year":"2023","unstructured":"Bram Wallace, Akash Gokul, and Nikhil Naik. 2023. EDICT: Exact diffusion inversion via coupled transformations. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 22532\u201322541. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10204740\/"},{"key":"e_1_3_3_126_2","article-title":"Wan: Open and advanced large-scale video generative models","author":"Wan Team","year":"2025","unstructured":"Team Wan, Ang Wang, Baole Ai, Bin Wen, Chaojie Mao, Chen-Wei Xie, Di Chen, Feiwu Yu, Haiming Zhao, Jianxiao Yang, et\u00a0al. 2025. Wan: Open and advanced large-scale video generative models. arXiv:2503.20314. Retrieved from https:\/\/arxiv.org\/abs\/2503.20314","journal-title":"arXiv:2503.20314"},{"key":"e_1_3_3_127_2","first-page":"1","volume-title":"Proceedings of the ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","author":"Wang Cong","year":"2025","unstructured":"Cong Wang, Jiaxi Gu, Panwen Hu, Xiao Dong, Yuanfan Guo, Hang Xu, and Xiaodan Liang. 2025. EasyControl: Adding control to video diffusion for controllable video generation and interpolation. In Proceedings of the ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 1\u20135. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10889997"},{"key":"e_1_3_3_128_2","article-title":"Larp: Tokenizing videos with a learned autoregressive generative prior","author":"Wang Hanyu","year":"2024","unstructured":"Hanyu Wang, Saksham Suri, Yixuan Ren, Hao Chen, and Abhinav Shrivastava. 2024. Larp: Tokenizing videos with a learned autoregressive generative prior. arXiv:2410.21264. Retrieved from https:\/\/arxiv.org\/abs\/2410.21264","journal-title":"arXiv:2410.21264"},{"key":"e_1_3_3_129_2","first-page":"28281","article-title":"Omnitokenizer: A joint image-video tokenizer for visual generation","volume":"37","author":"Wang Junke","year":"2024","unstructured":"Junke Wang, Yi Jiang, Zehuan Yuan, Bingyue Peng, Zuxuan Wu, and Yu-Gang Jiang. 2024. Omnitokenizer: A joint image-video tokenizer for visual generation. Advances in Neural Information Processing Systems 37 (2024), 28281\u201328295. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/31994923f58ae5b2d661b300bd439107-Abstract-Conference.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_130_2","article-title":"Modelscope text-to-video technical report","author":"Wang Jiuniu","year":"2023","unstructured":"Jiuniu Wang, Hangjie Yuan, Dayou Chen, Yingya Zhang, Xiang Wang, and Shiwei Zhang. 2023. Modelscope text-to-video technical report. arXiv:2308.06571. Retrieved from https:\/\/arxiv.org\/abs\/2308.06571","journal-title":"arXiv:2308.06571"},{"key":"e_1_3_3_131_2","first-page":"14549","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Wang Limin","year":"2023","unstructured":"Limin Wang, Bingkun Huang, Zhiyu Zhao, Zhan Tong, Yinan He, Yi Wang, Yali Wang, and Yu Qiao. 2023. Videomae v2: Scaling video masked autoencoders with dual masking. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 14549\u201314560. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10203656"},{"key":"e_1_3_3_132_2","article-title":"Framer: Interactive frame interpolation","author":"Wang Wen","year":"2024","unstructured":"Wen Wang, Qiuyu Wang, Kecheng Zheng, Hao Ouyang, Zhekai Chen, Biao Gong, Hao Chen, Yujun Shen, and Chunhua Shen. 2024. Framer: Interactive frame interpolation. arXiv:2410.18978. Retrieved from https:\/\/arxiv.org\/abs\/2410.18978","journal-title":"arXiv:2410.18978"},{"key":"e_1_3_3_133_2","article-title":"Cono: Consistency noise injection for tuning-free long video diffusion","author":"Wang Xingrui","year":"2024","unstructured":"Xingrui Wang, Xin Li, and Zhibo Chen. 2024. Cono: Consistency noise injection for tuning-free long video diffusion. arXiv:2406.05082. Retrieved from https:\/\/arxiv.org\/abs\/2406.05082","journal-title":"arXiv:2406.05082"},{"key":"e_1_3_3_134_2","first-page":"6572","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Wang Xiang","year":"2024","unstructured":"Xiang Wang, Shiwei Zhang, Hangjie Yuan, Zhiwu Qing, Biao Gong, Yingya Zhang, Yujun Shen, Changxin Gao, and Nong Sang. 2024. A recipe for scaling up text-to-video generation with text-free videos. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 6572\u20136582. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10657098"},{"key":"e_1_3_3_135_2","article-title":"Emu3: Next-token prediction is all you need","author":"Wang Xinlong","year":"2024","unstructured":"Xinlong Wang, Xiaosong Zhang, Zhengxiong Luo, Quan Sun, Yufeng Cui, Jinsheng Wang, Fan Zhang, Yueze Wang, Zhen Li, Qiying Yu, et\u00a0al. 2024. Emu3: Next-token prediction is all you need. arXiv:2409.18869. Retrieved from https:\/\/arxiv.org\/abs\/2409.18869","journal-title":"arXiv:2409.18869"},{"issue":"5","key":"e_1_3_3_136_2","doi-asserted-by":"crossref","first-page":"3059","DOI":"10.1007\/s11263-024-02295-1","article-title":"Lavie: High-quality video generation with cascaded latent diffusion models","volume":"133","author":"Wang Yaohui","year":"2025","unstructured":"Yaohui Wang, Xinyuan Chen, Xin Ma, Shangchen Zhou, Ziqi Huang, Yi Wang, Ceyuan Yang, Yinan He, Jiashuo Yu, Peiqing Yang, et\u00a0al. 2025. Lavie: High-quality video generation with cascaded latent diffusion models. International Journal of Computer Vision 133, 5 (2025), 3059\u20133078. Retrieved from https:\/\/link.springer.com\/article\/10.1007\/s11263-024-02295-1","journal-title":"International Journal of Computer Vision"},{"key":"e_1_3_3_137_2","first-page":"22922","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Wang Yuchi","year":"2025","unstructured":"Yuchi Wang, Junliang Guo, Xinyi Xie, Tianyu He, Xu Sun, and Jiang Bian. 2025. Vidtwin: Video VAE with decoupled structure and dynamics. In Proceedings of the Computer Vision and Pattern Recognition Conference. 22922\u201322932. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11092790"},{"key":"e_1_3_3_138_2","first-page":"13629","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Wang Yiping","year":"2025","unstructured":"Yiping Wang, Xuehai He, Kuan Wang, Luyao Ma, Jianwei Yang, Shuohang Wang, Simon Shaolei Du, and Yelong Shen. 2025. Is your world simulator a good story presenter? A consecutive events-based benchmark for future long video generation. In Proceedings of the Computer Vision and Pattern Recognition Conference. 13629\u201313638. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11093688\/"},{"key":"e_1_3_3_139_2","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.neucom.2022.10.008","article-title":"Video stabilization: A comprehensive survey","volume":"516","author":"Wang Yiming","year":"2023","unstructured":"Yiming Wang, Qian Huang, Chuanxu Jiang, Jiwen Liu, Mingzhou Shang, and Zhuang Miao. 2023. Video stabilization: A comprehensive survey. Neurocomputing 516 (2023), 205\u2013230. Retrieved from https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S092523122201270X","journal-title":"Neurocomputing"},{"key":"e_1_3_3_140_2","article-title":"Bridging continuous and discrete tokens for autoregressive visual generation","author":"Wang Yuqing","year":"2025","unstructured":"Yuqing Wang, Zhijie Lin, Yao Teng, Yuanzhi Zhu, Shuhuai Ren, Jiashi Feng, and Xihui Liu. 2025. Bridging continuous and discrete tokens for autoregressive visual generation. arXiv:2503.16430. Retrieved from https:\/\/arxiv.org\/abs\/2503.16430","journal-title":"arXiv:2503.16430"},{"key":"e_1_3_3_141_2","unstructured":"Yimu Wang Xuye Liu Wei Pang Li Ma Shuai Yuan Paul Debevec and Ning Yu. 2025. Survey of video diffusion models: Foundations implementations and applications. arxiv:2504.16081 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2504.16081"},{"key":"e_1_3_3_142_2","doi-asserted-by":"crossref","unstructured":"Yaohui Wang Xin Ma Xinyuan Chen Cunjian Chen Antitza Dantcheva Bo Dai and Yu Qiao. 2025. Leo: Generative latent image animator for human video synthesis. International Journal of Computer Vision 133 3 (2025) 1277\u20131289. Retrieved from https:\/\/link.springer.com\/article\/10.1007\/s11263-024-02231-3","DOI":"10.1007\/s11263-024-02231-3"},{"key":"e_1_3_3_143_2","article-title":"Loong: Generating minute-level long videos with autoregressive language models","author":"Wang Yuqing","year":"2024","unstructured":"Yuqing Wang, Tianwei Xiong, Daquan Zhou, Zhijie Lin, Yang Zhao, Bingyi Kang, Jiashi Feng, and Xihui Liu. 2024. Loong: Generating minute-level long videos with autoregressive language models. arXiv:2410.02757. Retrieved from https:\/\/arxiv.org\/abs\/2410.02757","journal-title":"arXiv:2410.02757"},{"key":"e_1_3_3_144_2","doi-asserted-by":"crossref","unstructured":"Zhendong Wang Yifan Jiang Huangjie Zheng Peihao Wang Pengcheng He Zhangyang Wang Weizhu Chen Mingyuan Zhou et\u00a0al. 2023. Patch diffusion: Faster and more data-efficient training of diffusion models. Advances in Neural Information Processing Systems 36 (2023) 72137\u201372154. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/hash\/e4667dd0a5a54b74019b72b677ed8ec1-Abstract-Conference.html","DOI":"10.52202\/075280-3158"},{"key":"e_1_3_3_145_2","first-page":"7395","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Weng Wenming","year":"2024","unstructured":"Wenming Weng, Ruoyu Feng, Yanhui Wang, Qi Dai, Chunyu Wang, Dacheng Yin, Zhiyuan Zhao, Kai Qiu, Jianmin Bao, Yuhui Yuan, et\u00a0al. 2024. Art-v: Auto-regressive text-to-video generation with diffusion models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 7395\u20137405. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10678076"},{"key":"e_1_3_3_146_2","article-title":"Nuwa-infinity: Autoregressive over autoregressive generation for infinite visual synthesis","author":"Wu Chenfei","year":"2022","unstructured":"Chenfei Wu, Jian Liang, Xiaowei Hu, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zicheng Liu, Yuejian Fang, and Nan Duan. 2022. Nuwa-infinity: Autoregressive over autoregressive generation for infinite visual synthesis. arXiv:2207.09814. Retrieved from https:\/\/arxiv.org\/abs\/2207.09814","journal-title":"arXiv:2207.09814"},{"key":"e_1_3_3_147_2","first-page":"720","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Wu Chenfei","year":"2022","unstructured":"Chenfei Wu, Jian Liang, Lei Ji, Fan Yang, Yuejian Fang, Daxin Jiang, and Nan Duan. 2022. N\u00fcwa: Visual synthesis pre-training for neural visual world creation. In Proceedings of the European Conference on Computer Vision. Springer, 720\u2013736. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-19787-1_41"},{"key":"e_1_3_3_148_2","first-page":"7623","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Wu Jay Zhangjie","year":"2023","unstructured":"Jay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei, Yuchao Gu, Yufei Shi, Wynne Hsu, Ying Shan, Xiaohu Qie, and Mike Zheng Shou. 2023. Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 7623\u20137633. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10376647"},{"key":"e_1_3_3_149_2","first-page":"18124","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Wu Pingyu","year":"2025","unstructured":"Pingyu Wu, Kai Zhu, Yu Liu, Liming Zhao, Wei Zhai, Yang Cao, and Zheng-Jun Zha. 2025. Improved video VAE for latent video diffusion model. In Proceedings of the Computer Vision and Pattern Recognition Conference. 18124\u201318133. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11093177"},{"key":"e_1_3_3_150_2","first-page":"378","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Wu Tianxing","year":"2024","unstructured":"Tianxing Wu, Chenyang Si, Yuming Jiang, Ziqi Huang, and Ziwei Liu. 2024. Freeinit: Bridging initialization gap in video diffusion models. In Proceedings of the European Conference on Computer Vision. Springer, 378\u2013394. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-72646-0_22"},{"key":"e_1_3_3_151_2","first-page":"23989","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Wu Ziyi","year":"2025","unstructured":"Ziyi Wu, Aliaksandr Siarohin, Willi Menapace, Ivan Skorokhodov, Yuwei Fang, Varnith Chordia, Igor Gilitschenski, and Sergey Tulyakov. 2025. Mind the time: Temporally-controlled multi-event video generation. In Proceedings of the Computer Vision and Pattern Recognition Conference. 23989\u201324000. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11095098"},{"issue":"4","key":"e_1_3_3_152_2","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.23919\/cje.2024.00.151","article-title":"A comprehensive survey on text-to-video generation","volume":"34","author":"Xie Fan","year":"2025","unstructured":"Fan Xie, Dan Zeng, Qiaomu Shen, and Bo Tang. 2025. A comprehensive survey on text-to-video generation. Chinese Journal of Electronics 34, 4 (2025), 1009\u20131036. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11151234","journal-title":"Chinese Journal of Electronics"},{"key":"e_1_3_3_153_2","first-page":"399","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Xing Jinbo","year":"2024","unstructured":"Jinbo Xing, Menghan Xia, Yong Zhang, Haoxin Chen, Wangbo Yu, Hanyuan Liu, Gongye Liu, Xintao Wang, Ying Shan, and Tien-Tsin Wong. 2024. Dynamicrafter: Animating open-domain images with video diffusion priors. In Proceedings of the European Conference on Computer Vision. Springer, 399\u2013417. Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-72952-2_23"},{"key":"e_1_3_3_154_2","article-title":"Large motion video autoencoding with cross-modal video VAE","author":"Xing Yazhou","year":"2024","unstructured":"Yazhou Xing, Yang Fei, Yingqing He, Jingye Chen, Jiaxin Xie, Xiaowei Chi, and Qifeng Chen. 2024. Large motion video autoencoding with cross-modal video VAE. arXiv:2412.17805. Retrieved from https:\/\/arxiv.org\/abs\/2412.17805","journal-title":"arXiv:2412.17805"},{"key":"e_1_3_3_155_2","first-page":"7827","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Xing Zhen","year":"2024","unstructured":"Zhen Xing, Qi Dai, Han Hu, Zuxuan Wu, and Yu-Gang Jiang. 2024. Simda: Simple diffusion adapter for efficient video generation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 7827\u20137839. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10657194"},{"issue":"2","key":"e_1_3_3_156_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3696415","article-title":"A survey on video diffusion models","volume":"57","author":"Xing Zhen","year":"2024","unstructured":"Zhen Xing, Qijun Feng, Haoran Chen, Qi Dai, Han Hu, Hang Xu, Zuxuan Wu, and Yu-Gang Jiang. 2024. A survey on video diffusion models. Comput. Surveys 57, 2 (2024), 1\u201342. DOI:https:\/\/dl.acm.org\/doi\/full\/10.1145\/3696415.","journal-title":"Comput. Surveys"},{"key":"e_1_3_3_157_2","article-title":"Autoregressive models in vision: A survey","author":"Xiong Jing","year":"2024","unstructured":"Jing Xiong, Gongye Liu, Lun Huang, Chengyue Wu, Taiqiang Wu, Yao Mu, Yuan Yao, Hui Shen, Zhongwei Wan, Jinfa Huang, et\u00a0al. 2024. Autoregressive models in vision: A survey. arXiv:2411.05902. Retrieved from https:\/\/arxiv.org\/abs\/2411.05902","journal-title":"arXiv:2411.05902"},{"key":"e_1_3_3_158_2","article-title":"Visionreward: Fine-grained multi-dimensional human preference learning for image and video generation","author":"Xu Jiazheng","year":"2024","unstructured":"Jiazheng Xu, Yu Huang, Jiale Cheng, Yuanming Yang, Jiajun Xu, Yuan Wang, Wenbo Duan, Shen Yang, Qunlin Jin, Shurun Li, et\u00a0al. 2024. Visionreward: Fine-grained multi-dimensional human preference learning for image and video generation. arXiv:2412.21059. Retrieved from https:\/\/arxiv.org\/abs\/2412.21059","journal-title":"arXiv:2412.21059"},{"key":"e_1_3_3_159_2","doi-asserted-by":"crossref","unstructured":"Haiwei Xue Xiangyang Luo Zhanghao Hu Xin Zhang Xunzhi Xiang Yuqin Dai Jianzhuang Liu Zhensong Zhang Minglei Li Jian Yang et\u00a0al. 2025. Human motion video generation: A survey. IEEE Transactions on Pattern Analysis & Machine Intelligence 47 11 (2025) 10709\u201310730. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11106267\/","DOI":"10.1109\/TPAMI.2025.3594034"},{"key":"e_1_3_3_160_2","doi-asserted-by":"crossref","unstructured":"Tianfan Xue Baian Chen Jiajun Wu Donglai Wei and William T. Freeman. 2019. Video enhancement with task-oriented flow. International Journal of Computer Vision 127 8 (2019) 1106\u20131125. Retrieved from https:\/\/link.springer.com\/article\/10.1007\/s11263-018-01144-2","DOI":"10.1007\/s11263-018-01144-2"},{"key":"e_1_3_3_161_2","article-title":"Videogpt: Video generation using vq-vae and transformers","author":"Yan Wilson","year":"2021","unstructured":"Wilson Yan, Yunzhi Zhang, Pieter Abbeel, and Aravind Srinivas. 2021. Videogpt: Video generation using vq-vae and transformers. arXiv:2104.10157. Retrieved from https:\/\/arxiv.org\/abs\/2104.10157","journal-title":"arXiv:2104.10157"},{"issue":"4","key":"e_1_3_3_162_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3626235","article-title":"Diffusion models: A comprehensive survey of methods and applications","volume":"56","author":"Yang Ling","year":"2023","unstructured":"Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang. 2023. Diffusion models: A comprehensive survey of methods and applications. Comput. Surveys 56, 4 (2023), 1\u201339. Retrieved from https:\/\/dl.acm.org\/doi\/full\/10.1145\/3626235","journal-title":"Comput. Surveys"},{"key":"e_1_3_3_163_2","article-title":"Rethinking video tokenization: A conditioned diffusion-based approach","author":"Yang Nianzu","year":"2025","unstructured":"Nianzu Yang, Pandeng Li, Liming Zhao, Yang Li, Chen-Wei Xie, Yehui Tang, Xudong Lu, Zhihang Liu, Yun Zheng, Yu Liu, et\u00a0al. 2025. Rethinking video tokenization: A conditioned diffusion-based approach. arXiv:2503.03708. Retrieved from https:\/\/arxiv.org\/abs\/2503.03708","journal-title":"arXiv:2503.03708"},{"key":"e_1_3_3_164_2","first-page":"1","volume-title":"SIGGRAPH Asia 2023 Conference Papers","author":"Yang Shuai","year":"2023","unstructured":"Shuai Yang, Yifan Zhou, Ziwei Liu, and Chen Change Loy. 2023. Rerender a video: Zero-shot text-guided video-to-video translation. In SIGGRAPH Asia 2023 Conference Papers. 1\u201311. Retrieved from https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3610548.3618160"},{"key":"e_1_3_3_165_2","unstructured":"Tao Yang Yangming Shi Yunwen Huang Feng Chen Yin Zheng and Lei Zhang. 2024. Factorized-Dreamer: Training A high-quality video generator with limited and low-quality data. arxiv:2408.10119 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2408.10119"},{"key":"e_1_3_3_166_2","article-title":"Cogvideox: Text-to-video diffusion models with an expert transformer","author":"Yang Zhuoyi","year":"2024","unstructured":"Zhuoyi Yang, Jiayan Teng, Wendi Zheng, Ming Ding, Shiyu Huang, Jiazheng Xu, Yuanming Yang, Wenyi Hong, Xiaohan Zhang, Guanyu Feng, et\u00a0al. 2024. Cogvideox: Text-to-video diffusion models with an expert transformer. arXiv:2408.06072. Retrieved from https:\/\/arxiv.org\/abs\/2408.06072","journal-title":"arXiv:2408.06072"},{"key":"e_1_3_3_167_2","article-title":"StyleMaster: Stylize your video with artistic generation and translation","author":"Ye Zixuan","year":"2024","unstructured":"Zixuan Ye, Huijuan Huang, Xintao Wang, Pengfei Wan, Di Zhang, and Wenhan Luo. 2024. StyleMaster: Stylize your video with artistic generation and translation. arXiv:2412.07744. Retrieved from https:\/\/arxiv.org\/abs\/2412.07744","journal-title":"arXiv:2412.07744"},{"key":"e_1_3_3_168_2","article-title":"Magic 1-For-1: Generating one minute video clips within one minute","author":"Yi Hongwei","year":"2025","unstructured":"Hongwei Yi, Shitong Shao, Tian Ye, Jiantong Zhao, Qingyu Yin, Michael Lingelbach, Li Yuan, Yonghong Tian, Enze Xie, and Daquan Zhou. 2025. Magic 1-For-1: Generating one minute video clips within one minute. arXiv:2502.07701. Retrieved from https:\/\/arxiv.org\/abs\/2502.07701","journal-title":"arXiv:2502.07701"},{"key":"e_1_3_3_169_2","article-title":"Nuwa-xl: Diffusion over diffusion for extremely long video generation","author":"Yin Shengming","year":"2023","unstructured":"Shengming Yin, Chenfei Wu, Huan Yang, Jianfeng Wang, Xiaodong Wang, Minheng Ni, Zhengyuan Yang, Linjie Li, Shuguang Liu, Fan Yang, et\u00a0al. 2023. Nuwa-xl: Diffusion over diffusion for extremely long video generation. arXiv:2303.12346. Retrieved from https:\/\/arxiv.org\/abs\/2303.12346","journal-title":"arXiv:2303.12346"},{"key":"e_1_3_3_170_2","first-page":"22963","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"Yin Tianwei","year":"2025","unstructured":"Tianwei Yin, Qiang Zhang, Richard Zhang, William T. Freeman, Fredo Durand, Eli Shechtman, and Xun Huang. 2025. From slow bidirectional to fast autoregressive video diffusion models. In Proceedings of the Computer Vision and Pattern Recognition Conference. 22963\u201322974. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/11092830"},{"key":"e_1_3_3_171_2","unstructured":"Jiwen Yu Yiran Qin Haoxuan Che Quande Liu Xintao Wang Pengfei Wan Di Zhang Kun Gai Hao Chen and Xihui Liu. 2025. A survey of interactive generative video. arxiv:2504.21853 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2504.21853"},{"key":"e_1_3_3_172_2","first-page":"8159","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Yu Jiyang","year":"2020","unstructured":"Jiyang Yu and Ravi Ramamoorthi. 2020. Learning video stabilization using optical flow. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 8159\u20138167. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/9156630\/"},{"key":"e_1_3_3_173_2","first-page":"10459","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Yu Lijun","year":"2023","unstructured":"Lijun Yu, Yong Cheng, Kihyuk Sohn, Jos\u00e9 Lezama, Han Zhang, Huiwen Chang, Alexander G. Hauptmann, Ming-Hsuan Yang, Yuan Hao, Irfan Essa, et\u00a0al. 2023. Magvit: Masked generative video transformer. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 10459\u201310469. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10205485"},{"key":"e_1_3_3_174_2","first-page":"52692","article-title":"SPAE: Semantic pyramid autoencoder for multimodal generation with frozen LLMs","volume":"36","author":"Yu Lijun","year":"2023","unstructured":"Lijun Yu, Yong Cheng, Zhiruo Wang, Vivek Kumar, Wolfgang Macherey, Yanping Huang, David Ross, Irfan Essa, Yonatan Bisk, Ming-Hsuan Yang, et\u00a0al. 2023. SPAE: Semantic pyramid autoencoder for multimodal generation with frozen LLMs. Advances in Neural Information Processing Systems 36 (2023), 52692\u201352704. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/hash\/a526cc8f6ffb74bedb6ff313e3fdb450-Abstract-Conference.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_175_2","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Yu Lijun","year":"2024","unstructured":"Lijun Yu, Jos\u00e9 Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G. Hauptmann, et\u00a0al. 2024. Language model beats diffusion-tokenizer is key to visual generation. In Proceedings of the International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_3_176_2","volume-title":"Proceedings of the 12th International Conference on Learning Representations, ICLR 2024","author":"Yu Sihyun","year":"2024","unstructured":"Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, and Anima Anandkumar. 2024. Efficient video diffusion models VIA content-frame motion-latent decomposition. In Proceedings of the 12th International Conference on Learning Representations, ICLR 2024. International Conference on Learning Representations, ICLR."},{"key":"e_1_3_3_177_2","first-page":"6463","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Yuan Hangjie","year":"2024","unstructured":"Hangjie Yuan, Shiwei Zhang, Xiang Wang, Yujie Wei, Tao Feng, Yining Pan, Yingya Zhang, Ziwei Liu, Samuel Albanie, and Dong Ni. 2024. Instructvideo: Instructing video diffusion models with human feedback. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 6463\u20136474. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10656991"},{"key":"e_1_3_3_178_2","first-page":"21236","article-title":"Chronomagic-bench: A benchmark for metamorphic evaluation of text-to-time-lapse video generation","volume":"37","author":"Yuan Shenghai","year":"2024","unstructured":"Shenghai Yuan, Jinfa Huang, Yongqi Xu, Yaoyang Liu, Shaofeng Zhang, Yujun Shi, Rui-Jie Zhu, Xinhua Cheng, Jiebo Luo, and Li Yuan. 2024. Chronomagic-bench: A benchmark for metamorphic evaluation of text-to-time-lapse video generation. Advances in Neural Information Processing Systems 37 (2024), 21236\u201321270. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/25b9960c8a5bd887eb5476c951260403-Abstract-Datasets_and_Benchmarks_Track.html","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_179_2","unstructured":"David Junhao Zhang Jay Zhangjie Wu Jia-Wei Liu Rui Zhao Lingmin Ran Yuchao Gu Difei Gao and Mike Zheng Shou. 2025. Show-1: Marrying pixel and latent diffusion models for text-to-video generation. arxiv:2309.15818 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2309.15818"},{"key":"e_1_3_3_180_2","article-title":"Flashvideo: Flowing fidelity to detail for efficient high-resolution video generation","author":"Zhang Shilong","year":"2025","unstructured":"Shilong Zhang, Wenbo Li, Shoufa Chen, Chongjian Ge, Peize Sun, Yida Zhang, Yi Jiang, Zehuan Yuan, Binyue Peng, and Ping Luo. 2025. Flashvideo: Flowing fidelity to detail for efficient high-resolution video generation. arXiv:2502.05179. Retrieved from https:\/\/arxiv.org\/abs\/2502.05179","journal-title":"arXiv:2502.05179"},{"key":"e_1_3_3_181_2","article-title":"I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models","author":"Zhang Shiwei","year":"2023","unstructured":"Shiwei Zhang, Jiayu Wang, Yingya Zhang, Kang Zhao, Hangjie Yuan, Zhiwu Qin, Xiang Wang, Deli Zhao, and Jingren Zhou. 2023. I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models. arXiv:2311.04145. Retrieved from https:\/\/arxiv.org\/abs\/2311.04145","journal-title":"arXiv:2311.04145"},{"key":"e_1_3_3_182_2","article-title":"Videomerge: Towards training-free long video generation","author":"Zhang Siyang","year":"2025","unstructured":"Siyang Zhang, Harry Yang, and Ser-Nam Lim. 2025. Videomerge: Towards training-free long video generation. arXiv:2503.09926. Retrieved from https:\/\/arxiv.org\/abs\/2503.09926","journal-title":"arXiv:2503.09926"},{"key":"e_1_3_3_183_2","article-title":"Open-sora: Democratizing efficient video production for all","author":"Zheng Zangwei","year":"2024","unstructured":"Zangwei Zheng, Xiangyu Peng, Tianji Yang, Chenhui Shen, Shenggui Li, Hongxin Liu, Yukun Zhou, Tianyi Li, and Yang You. 2024. Open-sora: Democratizing efficient video production for all. arXiv:2412.20404. Retrieved from https:\/\/arxiv.org\/abs\/2412.20404","journal-title":"arXiv:2412.20404"},{"key":"e_1_3_3_184_2","unstructured":"Daquan Zhou Weimin Wang Hanshu Yan Weiwei Lv Yizhe Zhu and Jiashi Feng. 2023. MagicVideo: Efficient video generation with latent diffusion models. arxiv:2211.11018 [cs.CV]. Retrieved from https:\/\/arxiv.org\/abs\/2211.11018"},{"key":"e_1_3_3_185_2","article-title":"A survey on generative AI and LLM for video generation, understanding, and streaming","author":"Zhou Pengyuan","year":"2024","unstructured":"Pengyuan Zhou, Lin Wang, Zhi Liu, Yanbin Hao, Pan Hui, Sasu Tarkoma, and Jussi Kangasharju. 2024. A survey on generative AI and LLM for video generation, understanding, and streaming. arXiv:2404.16038. Retrieved from https:\/\/arxiv.org\/abs\/2404.16038","journal-title":"arXiv:2404.16038"},{"key":"e_1_3_3_186_2","first-page":"2535","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhou Shangchen","year":"2024","unstructured":"Shangchen Zhou, Peiqing Yang, Jianyi Wang, Yihang Luo, and Chen Change Loy. 2024. Upscale-a-video: Temporal-consistent diffusion model for real-world video super-resolution. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2535\u20132545. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10655539"},{"key":"e_1_3_3_187_2","first-page":"2482","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Zhou Shangchen","year":"2019","unstructured":"Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, Wangmeng Zuo, and Jimmy Ren. 2019. Spatio-temporal filter adaptive network for video deblurring. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 2482\u20132491. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/9010007"},{"key":"e_1_3_3_188_2","first-page":"25399","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhou Xingyu","year":"2024","unstructured":"Xingyu Zhou, Leheng Zhang, Xiaorui Zhao, Keze Wang, Leida Li, and Shuhang Gu. 2024. Video super-resolution transformer with masked inter&intra-frame attention. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 25399\u201325408. Retrieved from https:\/\/ieeexplore.ieee.org\/abstract\/document\/10656731\/"},{"key":"e_1_3_3_189_2","article-title":"Golden noise for diffusion models: A learning framework","author":"Zhou Zikai","year":"2024","unstructured":"Zikai Zhou, Shitong Shao, Lichen Bai, Zhiqiang Xu, Bo Han, and Zeke Xie. 2024. Golden noise for diffusion models: A learning framework. arXiv:2411.09502. Retrieved from https:\/\/arxiv.org\/abs\/2411.09502","journal-title":"arXiv:2411.09502"},{"key":"e_1_3_3_190_2","unstructured":"Chang Zou Xuyang Liu Ting Liu Siteng Huang and Linfeng Zhang. 2025. Accelerating diffusion transformers with token-wise feature caching. In The Thirteenth International Conference on Learning Representations."},{"key":"e_1_3_3_191_2","article-title":"Edit-your-motion: Space-time diffusion decoupling learning for video motion editing","author":"Zuo Yi","year":"2024","unstructured":"Yi Zuo, Lingling Li, Licheng Jiao, Fang Liu, Xu Liu, Wenping Ma, Shuyuan Yang, and Yuwei Guo. 2024. Edit-your-motion: Space-time diffusion decoupling learning for video motion editing. arXiv:2405.04496. 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