{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T12:17:19Z","timestamp":1784031439803,"version":"3.55.0"},"reference-count":322,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T00:00:00Z","timestamp":1755648000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T00:00:00Z","timestamp":1755648000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"DOI":"10.1007\/s10462-025-11331-6","type":"journal-article","created":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T07:18:10Z","timestamp":1755674290000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Video diffusion generation: comprehensive review and open problems"],"prefix":"10.1007","volume":"58","author":[{"given":"Wenping","family":"Ma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoting","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Licheng","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingling","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Puhua","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuting","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengru","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Long","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruohan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueli","family":"Geng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuwei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuyuan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixi","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,20]]},"reference":[{"key":"11331_CR1","doi-asserted-by":"crossref","unstructured":"Akkerman R, Feng H, Black MJ, et\u00a0al (2024) Interdyn: controllable interactive dynamics with video diffusion models. arXiv preprint arXiv:2412.11785","DOI":"10.1109\/CVPR52734.2025.01163"},{"key":"11331_CR2","first-page":"23716","volume":"35","author":"JB Alayrac","year":"2022","unstructured":"Alayrac JB, Donahue J, Luc P et al (2022) Flamingo: a visual language model for few-shot learning. Adv Neural Inf Process Syst 35:23716\u201323736","journal-title":"Adv Neural Inf Process Syst"},{"key":"11331_CR3","unstructured":"An J, Zhang S, Yang H, et\u00a0al (2023) Latent-shift: Latent diffusion with temporal shift for efficient text-to-video generation. arXiv preprint arXiv:2304.08477"},{"key":"11331_CR4","unstructured":"Arkhipkin V, Shaheen Z, Vasilev V, et\u00a0al (2023) Fusionframes: efficient architectural aspects for text-to-video generation pipeline. arXiv preprint arXiv:2311.13073"},{"key":"11331_CR5","doi-asserted-by":"crossref","unstructured":"Bain M, Nagrani A, Varol G, et\u00a0al (2021) Frozen in time: A joint video and image encoder for end-to-end retrieval. In: ICCV","DOI":"10.1109\/ICCV48922.2021.00175"},{"key":"11331_CR6","unstructured":"Bai J, Xia M, Fu X, et\u00a0al (2025) Recammaster: Camera-controlled generative rendering from a single video. arXiv preprint arXiv:2503.11647"},{"key":"11331_CR7","unstructured":"Bai J, Xia M, Wang X, et\u00a0al (2024) Syncammaster: synchronizing multi-camera video generation from diverse viewpoints. arXiv preprint arXiv:2412.07760"},{"key":"11331_CR8","doi-asserted-by":"crossref","unstructured":"Bandyopadhyay H, Song YZ (2024) Flipsketch: Flipping static drawings to text-guided sketch animations. arXiv preprint arXiv:2411.10818","DOI":"10.1109\/CVPR52734.2025.02644"},{"key":"11331_CR9","doi-asserted-by":"crossref","unstructured":"Bar-Tal O, Chefer H, Tov O, et\u00a0al (2024) Lumiere: A space-time diffusion model for video generation. In: SIGGRAPH Asia 2024 Conference Papers, pp 1\u201311","DOI":"10.1145\/3680528.3687614"},{"key":"11331_CR10","unstructured":"Blattmann A, Dockhorn T, Kulal S, et\u00a0al (2023) Stable video diffusion: Scaling latent video diffusion models to large datasets. arXiv preprint arXiv:2311.15127"},{"key":"11331_CR11","doi-asserted-by":"crossref","unstructured":"Bu J, Ling P, Zhang P, et\u00a0al (2024) Broadway: Boost your text-to-video generation model in a training-free way. arXiv preprint arXiv:2410.06241","DOI":"10.1109\/CVPR52734.2025.01213"},{"key":"11331_CR12","doi-asserted-by":"crossref","unstructured":"Cai S, Ceylan D, Gadelha M, et\u00a0al (2024) Generative rendering: Controllable 4d-guided video generation with 2d diffusion models. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7611\u20137620","DOI":"10.1109\/CVPR52733.2024.00727"},{"key":"11331_CR13","doi-asserted-by":"crossref","unstructured":"Cai M, Cun X, Li X, et\u00a0al (2024) Ditctrl: Exploring attention control in multi-modal diffusion transformer for tuning-free multi-prompt longer video generation. arXiv:2412.18597","DOI":"10.1109\/CVPR52734.2025.00727"},{"key":"11331_CR14","unstructured":"Cao Y, Li S, Liu Y, et\u00a0al (2023) A comprehensive survey of AI-Generated Content (AIGC): A history of generative ai from gan to chatgpt. arXiv preprint arXiv:2303.04226"},{"key":"11331_CR15","unstructured":"Cao Y, Min X, Gao Y, et\u00a0al (2025) Agav-rater: Adapting large multimodal model for ai-generated audio-visual quality assessment. arXiv preprint arXiv:2501.18314"},{"key":"11331_CR16","unstructured":"Cao M, Mou C, Yuan Z, et\u00a0al (2024) Consistent human image and video generation with spatially conditioned diffusion. arXiv preprint arXiv:2412.14531"},{"key":"11331_CR17","unstructured":"Chang M, Prakash A, Gupta S (2023) Look ma, no hands! agent-environment factorization of egocentric videos. In: Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"11331_CR18","unstructured":"Chang D, Shi Y, Gao Q, et\u00a0al (2023) Magicdance: Realistic human dance video generation with motions & facial expressions transfer. CoRR"},{"issue":"6","key":"11331_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3687945","volume":"43","author":"H Chefer","year":"2024","unstructured":"Chefer H, Zada S, Paiss R et al (2024) Still-moving: customized video generation without customized video data. ACM Trans Grap (TOG) 43(6):1\u201311","journal-title":"ACM Trans Grap (TOG)"},{"key":"11331_CR20","doi-asserted-by":"crossref","unstructured":"Chen TS, Siarohin A, Menapace W, et\u00a0al (2024) Panda-70m: Captioning 70m videos with multiple cross-modality teachers. arXiv:2402.19479","DOI":"10.1109\/CVPR52733.2024.01265"},{"key":"11331_CR21","first-page":"24841","volume":"36","author":"Z Chen","year":"2023","unstructured":"Chen Z, Qing J, Zhou JH (2023) Cinematic mindscapes: high-quality video reconstruction from brain activity. Adv Neural Inf Process Syst 36:24841\u201324858","journal-title":"Adv Neural Inf Process Syst"},{"issue":"4","key":"11331_CR22","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s10462-025-11110-3","volume":"58","author":"H Chen","year":"2025","unstructured":"Chen H, Xiang Q, Hu J et al (2025) Comprehensive exploration of diffusion models in image generation: a survey. Artif Intell Rev 58(4):99","journal-title":"Artif Intell Rev"},{"key":"11331_CR23","unstructured":"Chen D, Hu J, Wei X, et\u00a0al (2024) Fine-gained zero-shot video sampling. arXiv preprint arXiv:2407.21475"},{"key":"11331_CR24","unstructured":"Chen W, Ji Y, Wu J, et\u00a0al (2024) Control-a-video: Controllable text-to-video diffusion models with motion prior and reward feedback learning. arXiv:2305.13840"},{"key":"11331_CR25","unstructured":"Chen W, Ji Y, Wu J, et\u00a0al (2024) Control-a-video: Controllable text-to-video diffusion models with motion prior and reward feedback learning. arXiv:2305.13840"},{"key":"11331_CR26","doi-asserted-by":"crossref","unstructured":"Chen X, Liu Z, Chen M, et\u00a0al (2024) Livephoto: Real image animation with text-guided motion control. In: European Conference on Computer Vision, Springer, Cham. pp 475\u2013491","DOI":"10.1007\/978-3-031-72649-1_27"},{"key":"11331_CR27","doi-asserted-by":"crossref","unstructured":"Chen J, Long F, An J, et\u00a0al (2025) Ouroboros-diffusion: Exploring consistent content generation in tuning-free long video diffusion. arXiv preprint arXiv:2501.09019","DOI":"10.1609\/aaai.v39i2.32205"},{"key":"11331_CR28","unstructured":"Chen C, Shu J, Chen L, et\u00a0al (2024) Motion-zero: Zero-shot moving object control framework for diffusion-based video generation. arXiv preprint arXiv:2401.10150"},{"key":"11331_CR29","unstructured":"Chen X, Wang X, Changpinyo S, et\u00a0al (2022) Pali: A jointly-scaled multilingual language-image model. arXiv preprint arXiv:2209.06794"},{"key":"11331_CR30","doi-asserted-by":"crossref","unstructured":"Chen Z, Wang Y, Wang F, et\u00a0al (2024) V3d: Video diffusion models are effective 3d generators. arXiv preprint arXiv:2403.06738","DOI":"10.1109\/TPAMI.2025.3581312"},{"key":"11331_CR31","unstructured":"Chen M, Wu C, Wang W, et\u00a0al (2023) Dragnuwa: Fine-grained control in video generation by integrating text, image, and trajectory. arXiv preprint arXiv:2308.07926"},{"key":"11331_CR32","doi-asserted-by":"crossref","unstructured":"Chen S, Xu M, Ren J, et\u00a0al (2024) Gentron: Diffusion transformers for image and video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 6441\u20136451","DOI":"10.1109\/CVPR52733.2024.00616"},{"key":"11331_CR33","unstructured":"Cho J, Puspitasari FD, Zheng S, et\u00a0al (2024) Sora as an agi world model? a complete survey on text-to-video generation. arXiv preprint arXiv:2403.05131"},{"issue":"4","key":"11331_CR34","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1145\/3386569.3392457","volume":"39","author":"M Chu","year":"2020","unstructured":"Chu M, Xie Y, Mayer J et al (2020) Learning temporal coherence via self-supervision for gan-based video generation. ACM Trans Graphics (TOG) 39(4):75. https:\/\/doi.org\/10.1145\/3386569.3392457","journal-title":"ACM Trans Graphics (TOG)"},{"key":"11331_CR35","doi-asserted-by":"crossref","unstructured":"\u00c7i\u00e7ek \u00d6, Abdulkadir A, Lienkamp SS, et\u00a0al (2016) 3d u-net: learning dense volumetric segmentation from sparse annotation. In: Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II 19, Springer, pp 424\u2013432","DOI":"10.1007\/978-3-319-46723-8_49"},{"key":"11331_CR36","doi-asserted-by":"crossref","unstructured":"Cordts M, et\u00a0al. (2016) The cityscapes dataset for semantic urban scene understanding. In: CVPR","DOI":"10.1109\/CVPR.2016.350"},{"issue":"9","key":"11331_CR37","doi-asserted-by":"publisher","first-page":"10850","DOI":"10.1109\/TPAMI.2023.3261988","volume":"45","author":"FA Croitoru","year":"2023","unstructured":"Croitoru FA, Hondru V, Ionescu RT et al (2023) Diffusion models in vision: a survey. IEEE Trans Pattern Anal Mach Intell 45(9):10850\u201310869. https:\/\/doi.org\/10.1109\/TPAMI.2023.3261988","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"11331_CR38","unstructured":"Dai Z, Zhang Z, Yao Y, et\u00a0al (2023) Animateanything: Fine-grained open domain image animation with motion guidance. arXiv preprint arXiv:2311.12886"},{"key":"11331_CR39","doi-asserted-by":"crossref","unstructured":"Damen D, et\u00a0al. (2018) Scaling egocentric vision: The epic-kitchens dataset. ECCV","DOI":"10.1007\/978-3-030-01225-0_44"},{"key":"11331_CR40","doi-asserted-by":"crossref","unstructured":"Danier D, Zhang F, Bull D (2023) Ldmvfi: Video frame interpolation with latent diffusion models. arXiv preprint arXiv:2303.09508","DOI":"10.1609\/aaai.v38i2.27912"},{"key":"11331_CR41","unstructured":"Dhariwal P, Nichol A (2021) Diffusion models beat gans on image synthesis. In: Advances in Neural Information Processing Systems, pp 8780\u20138794"},{"key":"11331_CR42","first-page":"332","volume-title":"Joint European conference on machine learning and knowledge discovery in databases","author":"Z Duan","year":"2024","unstructured":"Duan Z, You L, Wang C et al (2024) Diffsynth: latent in-iteration deflickering for realistic video synthesis. Joint European conference on machine learning and knowledge discovery in databases. Springer, Cham, pp 332\u2013347"},{"key":"11331_CR43","unstructured":"Ebert F, et\u00a0al. (2017) Self-supervised visual planning with temporal skip connections. In: CoRL"},{"key":"11331_CR44","first-page":"16222","volume-title":"Advances in Neural Information Processing Systems","author":"D Epstein","year":"2023","unstructured":"Epstein D, Jabri A, Poole B et al (2023) Diffusion self-guidance for controllable image generation. In: Oh A, Naumann T, Globerson A et al (eds) Advances in Neural Information Processing Systems, vol 36. Curran Associates Inc, New York, pp 16222\u201316239"},{"key":"11331_CR45","unstructured":"Fang Y, Xie Y, Liu Z, et\u00a0al (2023) Video-chatgpt: Towards detailed video understanding via large vision and language models. arXiv preprint arXiv:2306.05424"},{"key":"11331_CR46","doi-asserted-by":"crossref","unstructured":"Fei H, Wu S, Ji W, et\u00a0al (2024) Dysen-vdm: Empowering dynamics-aware text-to-video diffusion with llms. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7641\u20137653","DOI":"10.1109\/CVPR52733.2024.00730"},{"key":"11331_CR47","doi-asserted-by":"crossref","unstructured":"Feng W, Liu C, Liu S, et\u00a0al (2025) Blobgen-vid: Compositional text-to-video generation with blob video representations. arXiv preprint arXiv:2501.07647","DOI":"10.1109\/CVPR52734.2025.01212"},{"key":"11331_CR48","unstructured":"Feng M, Liu J, Yu K, et\u00a0al (2023) Dreamoving: A human video generation framework based on diffusion models. arXiv preprint arXiv:2312.05107"},{"key":"11331_CR49","doi-asserted-by":"crossref","unstructured":"Feng J, Ma A, Wang J, et\u00a0al (2024) Fancyvideo: Towards dynamic and consistent video generation via cross-frame textual guidance. arXiv preprint arXiv:2408.08189","DOI":"10.24963\/ijcai.2024\/1120"},{"key":"11331_CR50","unstructured":"Feng W, Wang X, Chen H, et\u00a0al (2024) Multi-sentence video grounding for long video generation. arXiv preprint arXiv:2407.13219"},{"key":"11331_CR51","unstructured":"Finn C, Abbeel P, Levine S (2017) Model-agnostic meta-learning for fast adaptation of deep networks. In: International conference on machine learning, PMLR, pp 1126\u20131135"},{"key":"11331_CR52","doi-asserted-by":"crossref","unstructured":"Fu TJ, Yu L, Zhang N, et\u00a0al (2023) Tell me what happened: Unifying text-guided video completion via multimodal masked video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 10681\u201310692","DOI":"10.1109\/CVPR52729.2023.01029"},{"key":"11331_CR53","unstructured":"Fuest M, Hu VT, Ommer B (2025) Maskflow: Discrete flows for flexible and efficient long video generation. arXiv preprint arXiv:2502.11234"},{"key":"11331_CR54","unstructured":"Fu X, Liu X, Wang X, et\u00a0al (2024a) Generative inbetweening. arXiv preprint arXiv:2412.07759"},{"key":"11331_CR55","unstructured":"Fu X, Liu X, Wang X, et\u00a0al (2024b) 3dtrajmaster: Mastering 3d trajectory for multi-entity motion in video generation. arXiv preprint arXiv:2412.07759"},{"key":"11331_CR56","unstructured":"Gao K, Shi J, Zhang H, et\u00a0al (2024) Vid-gpt: Introducing gpt-style autoregressive generation in video diffusion models. arXiv preprint arXiv:2406.10981"},{"key":"11331_CR57","doi-asserted-by":"crossref","unstructured":"Ge S, Hayes T, Yang H, et\u00a0al (2022) Long video generation with time-agnostic vqgan and time-sensitive transformer. In: European Conference on Computer Vision, Springer, pp 102\u2013118","DOI":"10.1007\/978-3-031-19790-1_7"},{"key":"11331_CR58","doi-asserted-by":"crossref","unstructured":"Ge S, Nah S, Liu G, et\u00a0al (2023) Preserve your own correlation: a noise prior for video diffusion models. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 22930\u201322941","DOI":"10.1109\/ICCV51070.2023.02096"},{"key":"11331_CR59","doi-asserted-by":"crossref","unstructured":"Geng D, Herrmann C, Hur J, et\u00a0al (2024) Motion prompting: Controlling video generation with motion trajectories. arXiv preprint arXiv:2412.02700","DOI":"10.1109\/CVPR52734.2025.00010"},{"key":"11331_CR60","doi-asserted-by":"crossref","unstructured":"Girdhar R, Singh M, Brown A, et\u00a0al (2024) Factorizing text-to-video generation by explicit image conditioning. In: European Conference on Computer Vision, Springer, pp 205\u2013224","DOI":"10.1007\/978-3-031-73033-7_12"},{"key":"11331_CR61","unstructured":"Gong L, Zhu Y, Li W, et\u00a0al (2024) Atomovideo: High fidelity image-to-video generation. arXiv preprint arXiv:2403.01800"},{"key":"11331_CR62","doi-asserted-by":"crossref","unstructured":"Goyal R, Kahou SE, Michalski V, et\u00a0al (2017) The \u201csomething something\u201d video database for learning and evaluating visual common sense. arXiv:1706.04261","DOI":"10.1109\/ICCV.2017.622"},{"key":"11331_CR63","unstructured":"Guo Y, Yang C, Rao A, et\u00a0al (2023) Animatediff: Animate your personalized text-to-image diffusion models without specific tuning. arXiv preprint arXiv:2307.04725"},{"key":"11331_CR64","doi-asserted-by":"crossref","unstructured":"Guo Y, Yang C, Rao A, et\u00a0al (2023) Sparsectrl: Adding sparse controls to text-to-video diffusion models. arXiv:2311.16933","DOI":"10.1007\/978-3-031-72946-1_19"},{"key":"11331_CR65","unstructured":"Guo J, Zhang D, Liu X, et\u00a0al (2024) Liveportrait: Efficient portrait animation with stitching and retargeting control. arXiv preprint arXiv:2407.03168"},{"key":"11331_CR66","doi-asserted-by":"crossref","unstructured":"Guo X, Zheng M, Hou L, et\u00a0al (2024) I2v-adapter: A general image-to-video adapter for diffusion models. In: ACM SIGGRAPH 2024 Conference Papers, pp 1\u201312","DOI":"10.1145\/3641519.3657407"},{"key":"11331_CR67","unstructured":"Gupta A, Tian S, Zhang Y, et\u00a0al (2022) Maskvit: Masked visual pre-training for video prediction. arXiv:2206.11894"},{"key":"11331_CR68","doi-asserted-by":"crossref","unstructured":"Gupta A, Yu L, Sohn K, et\u00a0al (2024) Photorealistic video generation with diffusion models. In: European Conference on Computer Vision, Springer, pp 393\u2013411","DOI":"10.1007\/978-3-031-72986-7_23"},{"key":"11331_CR69","unstructured":"Gu J, Wang S, Zhao H, et\u00a0al (2023) Reuse and diffuse: Iterative denoising for text-to-video generation. arXiv preprint arXiv:2309.03549"},{"key":"11331_CR70","unstructured":"Gu X, Wen C, Ye W, et\u00a0al (2023) Seer: Language instructed video prediction with latent diffusion models. arXiv preprint arXiv:2303.14897"},{"key":"11331_CR71","unstructured":"Haji-Ali M, Menapace W, Siarohin A, et\u00a0al (2024) Av-link: Temporally-aligned diffusion features for cross-modal audio-video generation. arXiv preprint arXiv:2412.15191"},{"key":"11331_CR72","doi-asserted-by":"publisher","first-page":"43563","DOI":"10.1109\/ACCESS.2020.2977684","volume":"8","author":"S Han","year":"2020","unstructured":"Han S, Xi Z (2020) Dynamic scene semantics slam based on semantic segmentation. IEEE Access 8:43563\u201343570","journal-title":"IEEE Access"},{"key":"11331_CR73","unstructured":"Harvey W, Naderiparizi S, Masrani V, et\u00a0al (2022) Flexible diffusion modeling of long videos. arXiv:2205.11495"},{"key":"11331_CR74","unstructured":"He B, Liao L, Wang W, et\u00a0al (2022) Vidm: Video implicit diffusion models. arXiv preprint arXiv:2212.00235"},{"key":"11331_CR75","unstructured":"He X, Liu Q, Qian S, et\u00a0al (2024) Id-animator: Zero-shot identity-preserving human video generation. arXiv preprint arXiv:2404.15275"},{"key":"11331_CR76","doi-asserted-by":"crossref","unstructured":"Henschel R, Khachatryan L, Hayrapetyan D, et\u00a0al (2024) Streamingt2v: Consistent, dynamic, and extendable long video generation from text. arXiv preprint arXiv:2403.14773","DOI":"10.1109\/CVPR52734.2025.00245"},{"key":"11331_CR77","unstructured":"Heusel M, Ramsauer H, Unterthiner T, et\u00a0al (2017) Gans trained by a two time-scale update rule converge to a local nash equilibrium. In: NeurIPS"},{"key":"11331_CR78","unstructured":"He Y, Xia M, Chen H, et\u00a0al (2023) Animate-a-story: Storytelling with retrieval-augmented video generation. arXiv preprint arXiv:2307.06940"},{"key":"11331_CR79","unstructured":"He Y, Yang T, Zhang Y, et\u00a0al (2022) Latent video diffusion models for high-fidelity video generation with arbitrary lengths. arXiv preprint arXiv:2211.13221"},{"key":"11331_CR80","first-page":"6840","volume-title":"Advances in Neural Information Processing Systems","author":"J Ho","year":"2020","unstructured":"Ho J, Jain A, Abbeel P (2020) Denoising diffusion probabilistic models. In: Larochelle H, Ranzato M, Hadsell R et al (eds) Advances in Neural Information Processing Systems, vol 33. Curran Associates Inc, New York, pp 6840\u20136851"},{"key":"11331_CR81","first-page":"8633","volume-title":"Advances in Neural Information Processing Systems","author":"J Ho","year":"2022","unstructured":"Ho J, Salimans T, Gritsenko A et al (2022) Video diffusion models. In: Koyejo S, Mohamed S, Agarwal A et al (eds) Advances in Neural Information Processing Systems, vol 35. Curran Associates Inc, New York, pp 8633\u20138646"},{"key":"11331_CR82","unstructured":"Ho J, Chan W, Saharia C, et\u00a0al (2022) Imagen video: High definition video generation with diffusion models. arXiv preprint arXiv:2210.02303"},{"key":"11331_CR83","unstructured":"Hong W, Ding M, Zheng W, et\u00a0al (2022) Cogvideo: Large-scale pretraining for text-to-video generation via transformers. arXiv preprint arXiv:2205.15868"},{"key":"11331_CR84","unstructured":"Hong S, Kemelmacher-Shlizerman I, Curless B, et\u00a0al (2025) Musicinfuser: Making video diffusion listen and dance. arXiv preprint arXiv:2503.14505"},{"key":"11331_CR85","unstructured":"H\u00f6ppe T, Mehrjou A, Bauer S, et\u00a0al (2022) Diffusion models for video prediction and infilling. arXiv:2206.07696"},{"key":"11331_CR86","doi-asserted-by":"crossref","unstructured":"Hore A, Ziou D (2010) Image quality metrics: Psnr vs. ssim. 2010 20th International Conference on Pattern Recognition pp 2366\u20132369","DOI":"10.1109\/ICPR.2010.579"},{"key":"11331_CR87","unstructured":"Houlsby N, Giurgiu A, Jastrzebski S, et\u00a0al (2019) Parameter-efficient transfer learning for nlp. In: International conference on machine learning, PMLR, pp 2790\u20132799"},{"key":"11331_CR88","unstructured":"Hou C, Wei G, Zeng Y, et\u00a0al (2024) Training-free camera control for video generation. arXiv preprint arXiv:2406.10126"},{"issue":"2","key":"11331_CR89","first-page":"3","volume":"1","author":"EJ Hu","year":"2022","unstructured":"Hu EJ, Shen Y, Wallis P et al (2022) Lora: low-rank adaptation of large language models. ICLR 1(2):3","journal-title":"ICLR"},{"key":"11331_CR90","unstructured":"Huang HP, Su YC, Sun D, et\u00a0al (2023) Fine-grained controllable video generation via object appearance and context. arXiv:2312.02919"},{"key":"11331_CR91","unstructured":"Huang Y, Zheng W, Gao Y, et\u00a0al (2024) Owl-1: Omni world model for consistent long video generation. arXiv preprint arXiv:2412.09600"},{"key":"11331_CR92","unstructured":"Hu Y, Chen Z, Luo C (2023) Lamd: Latent motion diffusion for video generation. arXiv preprint arXiv:2304.11603"},{"key":"11331_CR93","unstructured":"Hu L, Gao X, Zhang P, et\u00a0al (2024) Animate anyone: consistent and controllable image-to-video synthesis for character animation. arXiv:2311.17117"},{"key":"11331_CR94","unstructured":"Hu J, Zhong T, Wang X, et\u00a0al (2024) Vivid-10m: a dataset and baseline for versatile and interactive video local editing. arXiv:2411.15260"},{"key":"11331_CR95","doi-asserted-by":"crossref","unstructured":"Jain Y, Nasery A, Vineet V, et\u00a0al (2024) Peekaboo: interactive video generation via masked-diffusion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 8079\u20138088","DOI":"10.1109\/CVPR52733.2024.00772"},{"key":"11331_CR96","doi-asserted-by":"crossref","unstructured":"Jeong Y, Ryoo W, Lee S, et\u00a0al (2023) The power of sound (tpos): audio reactive video generation with stable diffusion. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 7822\u20137832","DOI":"10.1109\/ICCV51070.2023.00719"},{"key":"11331_CR97","unstructured":"Jiang J, Hong G, Zhou L, et\u00a0al (2024) Dive: Dit-based video generation with enhanced control. arXiv preprint arXiv:2409.01595"},{"key":"11331_CR98","doi-asserted-by":"crossref","unstructured":"Jiang Y, Wu T, Yang S, et\u00a0al (2023) Videobooth: diffusion-based video generation with image prompts. arXiv:2312.00777","DOI":"10.1109\/CVPR52733.2024.00639"},{"key":"11331_CR99","doi-asserted-by":"crossref","unstructured":"Jiang Y, Wu T, Yang S, et\u00a0al (2024) Videobooth: diffusion-based video generation with image prompts. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 6689\u20136700","DOI":"10.1109\/CVPR52733.2024.00639"},{"key":"11331_CR100","doi-asserted-by":"crossref","unstructured":"Jiang Y, Yang S, Koh TL, et\u00a0al (2023) Text2performer: text-driven human video generation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 22747\u201322757","DOI":"10.1109\/ICCV51070.2023.02079"},{"key":"11331_CR101","doi-asserted-by":"crossref","unstructured":"Kandala H, Gao J, Yang J (2024) Pix2gif: Motion-guided diffusion for gif generation. In: European Conference on Computer Vision, Springer, pp 35\u201351","DOI":"10.1007\/978-3-031-73013-9_3"},{"key":"11331_CR102","doi-asserted-by":"crossref","unstructured":"Karras J, Holynski A, Wang TC, et\u00a0al (2023) Dreampose: Fashion image-to-video synthesis via stable diffusion. In: 2023 IEEE\/CVF International conference on computer vision (ICCV), IEEE, pp 22623\u201322633","DOI":"10.1109\/ICCV51070.2023.02073"},{"key":"11331_CR103","unstructured":"Kay W, Carreira J, Simonyan K, et\u00a0al (2017) The kinetics human action video dataset. arXiv:1705.06950"},{"key":"11331_CR104","doi-asserted-by":"crossref","unstructured":"Khachatryan L, Movsisyan A, Tadevosyan V, et\u00a0al (2023) Text2video-zero: Text-to-image diffusion models are zero-shot video generators. arXiv preprint arXiv:2303.13439","DOI":"10.1109\/ICCV51070.2023.01462"},{"key":"11331_CR105","unstructured":"Kim J, Kang J, Choi J, et\u00a0al (2024) Fifo-diffusion: generating infinite videos from text without training. arXiv:2405.11473"},{"key":"11331_CR106","doi-asserted-by":"crossref","unstructured":"Kim K, Lee H, Park J, et\u00a0al (2024) Hybrid video diffusion models with 2d triplane and 3d wavelet representation. arXiv preprint arXiv:2402.13729","DOI":"10.1007\/978-3-031-72943-0_9"},{"key":"11331_CR107","unstructured":"Kong W, Tian Q, Zhang Z, et\u00a0al (2024) Hunyuanvideo: a systematic framework for large video generative models. arXiv preprint arXiv:2412.03603"},{"key":"11331_CR108","doi-asserted-by":"crossref","unstructured":"Kwon M, Oh SW, Zhou Y, et\u00a0al (2024) Harivo: harnessing text-to-image models for video generation. In: European Conference on Computer Vision, Springer, pp 19\u201336","DOI":"10.1007\/978-3-031-73668-1_2"},{"key":"11331_CR109","unstructured":"Lapid A, Achituve I, Bracha L, et\u00a0al (2023) Gd-vdm: generated depth for better diffusion-based video generation. arXiv preprint arXiv:2306.11173"},{"key":"11331_CR110","unstructured":"Lee S, Kong C, Jeon D, et\u00a0al (2023) Aadiff: audio-aligned video synthesis with text-to-image diffusion. arXiv:2305.04001"},{"key":"11331_CR111","doi-asserted-by":"crossref","unstructured":"Lee T, Kwon S, Kim T (2024) Grid diffusion models for text-to-video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 8734\u20138743","DOI":"10.1109\/CVPR52733.2024.00834"},{"key":"11331_CR112","doi-asserted-by":"crossref","unstructured":"Lester B, Al-Rfou R, Constant N (2021) The power of scale for parameter-efficient prompt tuning. arXiv:2104.08691","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"11331_CR113","unstructured":"Liang J, et\u00a0al. (2022) Make your video: High-resolution text-to-video generation with latent diffusion models. CVPR"},{"key":"11331_CR114","first-page":"56","volume-title":"European conference on computer vision","author":"J Liang","year":"2024","unstructured":"Liang J, Fan Y, Zhang K et al (2024) Movideo: motion-aware video generation with diffusion model. European conference on computer vision. Springer, Cham, pp 56\u201374"},{"key":"11331_CR115","unstructured":"Liang Z, Zhang Y, Liu Y, et\u00a0al (2023) Leo: Generative latent image animator for human video synthesis. arXiv preprint arXiv:2305.03989"},{"key":"11331_CR116","unstructured":"Li W, Cao Y, Su X, et\u00a0al (2024) Decoupled video generation with chain of training-free diffusion model experts. https:\/\/arxiv.org\/abs\/2408.13423, arXiv:2408.13423"},{"key":"11331_CR117","unstructured":"Li X, Chu W, Wu Y, et\u00a0al (2023) Videogen: a reference-guided latent diffusion approach for high definition text-to-video generation. arXiv preprint arXiv:2309.00398"},{"key":"11331_CR118","unstructured":"Li W, Gong L, Zhu Y, et\u00a0al (2024) Tuning-free noise rectification for high fidelity image-to-video generation. arXiv preprint arXiv:2403.02827"},{"key":"11331_CR119","unstructured":"Li C, Huang D, Lu Z, et\u00a0al (2024) A survey on long video generation: challenges, methods, and prospects. arXiv preprint arXiv:2403.16407"},{"key":"11331_CR120","unstructured":"Li Z, Hu S, Liu S, et\u00a0al (2024) Arlon: Boosting diffusion transformers with autoregressive models for long video generation. arXiv preprint arXiv:2410.20502"},{"key":"11331_CR121","doi-asserted-by":"crossref","unstructured":"Li Z, Lin B, Ye Y, et\u00a0al (2024) Wf-vae: enhancing video vae by wavelet-driven energy flow for latent video diffusion model. arXiv preprint arXiv:2411.17459","DOI":"10.1109\/CVPR52734.2025.01656"},{"key":"11331_CR122","unstructured":"Li J, Li D, Savarese S, et\u00a0al (2023) Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In: International conference on machine learning, PMLR, pp 19730\u201319742"},{"key":"11331_CR123","unstructured":"Li J, Li D, Xiong C, et\u00a0al (2022) Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. In: International conference on machine learning, PMLR, pp 12888\u201312900"},{"key":"11331_CR124","unstructured":"Ling P, Bu J, Zhang P, et\u00a0al (2024) Motionclone: training-free motion cloning for controllable video generation. arXiv:2406.05338"},{"key":"11331_CR125","unstructured":"Lin H, Zala A, Cho J, et\u00a0al (2023) Videodirectorgpt: Consistent multi-scene video generation via llm-guided planning. arXiv preprint arXiv:2309.15091"},{"key":"11331_CR126","doi-asserted-by":"crossref","unstructured":"Li Z, Tucker R, Snavely N, et\u00a0al (2024) Generative image dynamics. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 24142\u201324153","DOI":"10.1109\/CVPR52733.2024.02279"},{"key":"11331_CR127","doi-asserted-by":"crossref","unstructured":"Liu Y, Cun X, Liu X, et\u00a0al (2024) Evalcrafter: benchmarking and evaluating large video generation models. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 22139\u201322149","DOI":"10.1109\/CVPR52733.2024.02090"},{"key":"11331_CR128","unstructured":"Liu B, Liu X, Dai A, et\u00a0al (2023) Dual-stream diffusion net for text-to-video generation. arXiv preprint arXiv:2308.08316"},{"key":"11331_CR129","unstructured":"Liu C, Li R, Zhang K, et\u00a0al (2024) Stablev2v: stablizing shape consistency in video-to-video editing. arXiv preprint arXiv:2411.11045"},{"key":"11331_CR130","unstructured":"Liu Y, Ren Y, Cun X, et\u00a0al (2024) Redefining temporal modeling in video diffusion: the vectorized timestep approach. arXiv preprint arXiv:2410.03160"},{"key":"11331_CR131","doi-asserted-by":"crossref","unstructured":"Liu S, Ren Z, Gupta S, et\u00a0al (2024) Physgen: rigid-body physics-grounded image-to-video generation. In: European Conference on Computer Vision, Springer, pp 360\u2013378","DOI":"10.1007\/978-3-031-73007-8_21"},{"key":"11331_CR132","unstructured":"Liu F, Sun W, Wang H, et\u00a0al (2024) Reconx: Reconstruct any scene from sparse views with video diffusion model. arXiv preprint arXiv:2408.16767"},{"key":"11331_CR133","unstructured":"Liu X, Su K, Shlizerman E (2024) Tell what you hear from what you see\u2013video to audio generation through text. arXiv preprint arXiv:2411.05679"},{"key":"11331_CR134","doi-asserted-by":"crossref","unstructured":"Liu J, Wang W, Liu W, et\u00a0al (2023) Ed-t2v: An efficient training framework for diffusion-based text-to-video generation. In: 2023 International Joint Conference on Neural Networks (IJCNN), IEEE, pp 1\u20138, URL https:\/\/ieeexplore.ieee.org\/abstract\/document\/10191565","DOI":"10.1109\/IJCNN54540.2023.10191565"},{"key":"11331_CR135","unstructured":"Liu H, Yang X, Zhou N, et\u00a0al (2023) Animatediff: Animate your personalized text-to-image diffusion models without specific tuning. arXiv preprint arXiv:2307.04725"},{"key":"11331_CR136","unstructured":"Liu H, Yan W, Zaharia M, et\u00a0al (2025) World model on million-length video and language with blockwise ringattention. arXiv:2402.08268"},{"key":"11331_CR137","unstructured":"Li Y, Wang X, Zhang Z, et\u00a0al (2024) Image conductor: Precision control for interactive video synthesis. arXiv preprint arXiv:2406.15339"},{"key":"11331_CR138","doi-asserted-by":"crossref","unstructured":"Li H, Xu M, Zhan Y, et\u00a0al (2025) Openhumanvid: A large-scale high-quality dataset for enhancing human-centric video generation. arXiv:2412.00115","DOI":"10.1109\/CVPR52734.2025.00726"},{"key":"11331_CR139","doi-asserted-by":"crossref","unstructured":"Li X, Zhang Y, Ye X (2024) Drivingdiffusion: Layout-guided multi-view driving scenarios video generation with latent diffusion model. In: European Conference on Computer Vision, Springer, pp 469\u2013485","DOI":"10.1007\/978-3-031-73229-4_27"},{"key":"11331_CR140","unstructured":"Li W, Zhao S, Mou C, et\u00a0al (2024) Omnidrag: Enabling motion control for omnidirectional image-to-video generation. arXiv preprint arXiv:2412.09623"},{"key":"11331_CR141","doi-asserted-by":"crossref","unstructured":"Long F, Qiu Z, Yao T, et\u00a0al (2024) Videostudio: Generating consistent-content and multi-scene videos. In: European Conference on Computer Vision, Springer, pp 468\u2013485","DOI":"10.1007\/978-3-031-73027-6_27"},{"key":"11331_CR142","unstructured":"Lu Y, Liang Y, Zhu L, et\u00a0al (2024) Freelong: Training-free long video generation with spectralblend temporal attention. arXiv:2407.19918"},{"key":"11331_CR143","doi-asserted-by":"crossref","unstructured":"Luo Z, Chen D, Zhang Y, et\u00a0al (2023) Videofusion: Decomposed diffusion models for high-quality video generation. arXiv preprint arXiv:2303.08320","DOI":"10.1109\/CVPR52729.2023.00984"},{"key":"11331_CR144","unstructured":"Lu H, Yang G, Fei N, et\u00a0al (2023) Vdt: General-purpose video diffusion transformers via mask modeling. arXiv preprint arXiv:2305.13311"},{"key":"11331_CR145","unstructured":"Lu Y, Zhu L, Fan H, et\u00a0al (2023) Flowzero: Zero-shot text-to-video synthesis with llm-driven dynamic scene syntax. arXiv preprint arXiv:2311.15813"},{"key":"11331_CR146","doi-asserted-by":"crossref","unstructured":"Lv J, Huang Y, Yan M, et\u00a0al (2024) Gpt4motion: Scripting physical motions in text-to-video generation via blender-oriented gpt planning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 1430\u20131440","DOI":"10.1109\/CVPRW63382.2024.00150"},{"key":"11331_CR147","doi-asserted-by":"crossref","unstructured":"Ma WDK, Lewis JP, Kleijn WB (2024) Trailblazer: Trajectory control for diffusion-based video generation. In: SIGGRAPH Asia 2024 Conference Papers, pp 1\u201311","DOI":"10.1145\/3680528.3687652"},{"key":"11331_CR148","unstructured":"Ma Y, Chen J, Di D, et\u00a0al (2025) Tuning-free long video generation via global-local collaborative diffusion. arXiv preprint arXiv:2501.05484"},{"key":"11331_CR149","doi-asserted-by":"crossref","unstructured":"Ma Y, He Y, Cun X, et\u00a0al (2024) Follow your pose: Pose-guided text-to-video generation using pose-free videos. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp 4117\u20134125","DOI":"10.1609\/aaai.v38i5.28206"},{"key":"11331_CR150","unstructured":"Ma Y, He Y, Wang H, et\u00a0al (2024) Follow-your-click: Open-domain regional image animation via short prompts. arXiv preprint arXiv:2403.08268"},{"key":"11331_CR151","doi-asserted-by":"crossref","unstructured":"Mao Y, Shen X, Zhang J, et\u00a0al (2024) Tavgbench: Benchmarking text to audible-video generation. In: Proceedings of the 32nd ACM International Conference on Multimedia, pp 6607\u20136616","DOI":"10.1145\/3664647.3680612"},{"key":"11331_CR152","unstructured":"Materzynska J, Sivic J, Shechtman E, et\u00a0al (2023) Customizing motion in text-to-video diffusion models. arXiv preprint arXiv:2312.04966"},{"key":"11331_CR153","doi-asserted-by":"crossref","unstructured":"Ma X, Wang Y, Jia G, et\u00a0al (2024) Cinemo: Consistent and controllable image animation with motion diffusion models. arXiv preprint arXiv:2407.15642","DOI":"10.1109\/CVPR52734.2025.00683"},{"key":"11331_CR154","unstructured":"Ma X, Wang Y, Jia G, et\u00a0al (2024) Latte: Latent diffusion transformer for video generation. arXiv preprint arXiv:2401.03048"},{"key":"11331_CR155","doi-asserted-by":"crossref","unstructured":"Ma Z, Zhou D, Yeh CH, et\u00a0al (2024) Magic-me: Identity-specific video customized diffusion. arXiv:2402.09368","DOI":"10.1007\/978-3-031-92808-6_2"},{"key":"11331_CR156","doi-asserted-by":"crossref","unstructured":"Menapace W, Siarohin A, Skorokhodov I, et\u00a0al (2024) Snap video: Scaled spatiotemporal transformers for text-to-video synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7038\u20137048","DOI":"10.1109\/CVPR52733.2024.00672"},{"key":"11331_CR157","doi-asserted-by":"crossref","unstructured":"Miech A, Zhukov D, Alayrac JB, et\u00a0al (2019) Howto100m: Learning a text-video embedding by watching hundred million narrated video clips. In: ICCV","DOI":"10.1109\/ICCV.2019.00272"},{"key":"11331_CR158","doi-asserted-by":"crossref","unstructured":"Moon G, Shiraotri T, Saito S (2024) Expressive whole-body 3d gaussian avatar. In: European Conference on Computer Vision (ECCV), https:\/\/mks0601.github.io\/ExAvatar\/","DOI":"10.1007\/978-3-031-72940-9_2"},{"key":"11331_CR159","unstructured":"Namekata K, Bahmani S, Wu Z, et\u00a0al (2025) Sg-i2v: Self-guided trajectory control in image-to-video generation. arXiv:2411.04989"},{"key":"11331_CR160","unstructured":"Nan K, Xie R, Zhou P, et\u00a0al (2025) Openvid-1m: A large-scale high-quality dataset for text-to-video generation. arXiv:2407.02371"},{"key":"11331_CR161","doi-asserted-by":"crossref","unstructured":"Ni H, Egger B, Lohit S, et\u00a0al (2024) Ti2v-zero: Zero-shot image conditioning for text-to-video diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 9015\u20139025","DOI":"10.1109\/CVPR52733.2024.00861"},{"key":"11331_CR162","doi-asserted-by":"crossref","unstructured":"Ni H, Shi C, Li K, et\u00a0al (2023) Conditional image-to-video generation with latent flow diffusion models. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 18444\u201318455","DOI":"10.1109\/CVPR52729.2023.01769"},{"key":"11331_CR163","first-page":"111","volume-title":"European conference on computer vision","author":"M Niu","year":"2024","unstructured":"Niu M, Cun X, Wang X et al (2024) Mofa-video: controllable image animation via generative motion field adaptions in frozen image-to-video diffusion model. European conference on computer vision. Springer, Cham, pp 111\u2013128"},{"key":"11331_CR164","first-page":"401","volume-title":"European Conference on computer vision","author":"G Oh","year":"2024","unstructured":"Oh G, Jeong J, Kim S et al (2024) Mevg: multi-event video generation with text-to-video models. European Conference on computer vision. Springer, Cham, pp 401\u2013418"},{"key":"11331_CR165","unstructured":"Ouyang Y, Yuan J, Zhao H, et\u00a0al (2024) Flexifilm: Long video generation with flexible conditions. arXiv preprint arXiv:2404.18620"},{"key":"11331_CR166","unstructured":"Pan B, Xu Z, Huang CHP, et\u00a0al (2024) Actanywhere: Subject-aware video background generation. arXiv:2401.10822"},{"key":"11331_CR167","doi-asserted-by":"crossref","unstructured":"Peng B, Chen X, Wang Y, et\u00a0al (2024) Conditionvideo: training-free condition-guided video generation. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp 4459\u20134467","DOI":"10.1609\/aaai.v38i5.28244"},{"key":"11331_CR168","unstructured":"Peng B, Wang J, Zhang Y, et\u00a0al (2025) Controlnext: Powerful and efficient control for image and video generation. arXiv:2408.06070"},{"key":"11331_CR169","doi-asserted-by":"crossref","unstructured":"Perazzi F, et\u00a0al. (2016) A benchmark dataset and evaluation methodology for video object segmentation. In: CVPR","DOI":"10.1109\/CVPR.2016.85"},{"key":"11331_CR170","doi-asserted-by":"publisher","unstructured":"Pradhyumna P, Shreya G, et\u00a0al (2021) Graph Neural Network (GNN) in image and video understanding using deep learning for computer vision applications. In: 2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC), IEEE, pp 1183\u20131189, https:\/\/doi.org\/10.1109\/ICESC51422.2021.9532631","DOI":"10.1109\/ICESC51422.2021.9532631"},{"key":"11331_CR171","doi-asserted-by":"crossref","unstructured":"Qing Z, Zhang S, Wang J, et\u00a0al (2024) Hierarchical spatio-temporal decoupling for text-to-video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 6635\u20136645","DOI":"10.1109\/CVPR52733.2024.00634"},{"key":"11331_CR172","unstructured":"Qin B, Ye W, Yu Q, et\u00a0al (2023) Dancing avatar: Pose and text-guided human motion videos synthesis with image diffusion model. https:\/\/arxiv.org\/abs\/2308.07749, arXiv:2308.07749"},{"key":"11331_CR173","unstructured":"Qiu H, Chen Z, Wang Z, et\u00a0al (2024) Freetraj: Tuning-free trajectory control in video diffusion models. arXiv preprint arXiv:2406.16863"},{"key":"11331_CR174","unstructured":"Qiu H, Xia M, Zhang Y, et\u00a0al (2023) Freenoise: Tuning-free longer video diffusion via noise rescheduling. arXiv preprint arXiv:2310.15169arXiv:2310.15169"},{"key":"11331_CR175","doi-asserted-by":"crossref","unstructured":"Qu Q, Shen Y, Chen X, et\u00a0al (2024) E2hqv: High-quality video generation from event camera via theory-inspired model-aided deep learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp 4632\u20134640","DOI":"10.1609\/aaai.v38i5.28263"},{"key":"11331_CR176","unstructured":"Radford A, Kim JW, Hallacy C, et\u00a0al (2021) Learning transferable visual models from natural language supervision. In: ICML"},{"key":"11331_CR177","unstructured":"Ren W, Yang H, Zhang G, et\u00a0al (2024) Consisti2v: Enhancing visual consistency for image-to-video generation. arXiv preprint arXiv:2402.04324"},{"key":"11331_CR178","unstructured":"Rings F (2024) Stableanimator: High-quality identity-preserving human image animation. arXiv preprint arXiv:2411.17697"},{"key":"11331_CR179","doi-asserted-by":"crossref","unstructured":"Rombach R, Blattmann A, Lorenz D, et\u00a0al (2022) High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 10684\u201310695","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"11331_CR180","doi-asserted-by":"crossref","unstructured":"Ruan L, Ma Y, Yang H, et\u00a0al (2023) Mm-diffusion: Learning multi-modal diffusion models for joint audio and video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 10219\u201310228","DOI":"10.1109\/CVPR52729.2023.00985"},{"key":"11331_CR181","doi-asserted-by":"crossref","unstructured":"Ruan L, Ma Y, Yang H, et\u00a0al (2023) Mm-diffusion: Learning multi-modal diffusion models for joint audio and video generation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10219\u201310228","DOI":"10.1109\/CVPR52729.2023.00985"},{"key":"11331_CR182","unstructured":"Ryan P, Bandurski J, Bals J, et\u00a0al (2023) Evaluating text-to-video generation with kernel video distance. In: CVPR"},{"key":"11331_CR183","first-page":"36479","volume":"35","author":"C Saharia","year":"2022","unstructured":"Saharia C, Chan W, Saxena S et al (2022) Photorealistic text-to-image diffusion models with deep language understanding. Adv Neural Inf Process Syst 35:36479\u201336494","journal-title":"Adv Neural Inf Process Syst"},{"key":"11331_CR184","doi-asserted-by":"crossref","unstructured":"Saito M, Matsumoto E, Saito S (2017) Tgan: Temporal generative adversarial nets with singular value clipping. In: ICCV","DOI":"10.1109\/ICCV.2017.308"},{"key":"11331_CR185","doi-asserted-by":"crossref","unstructured":"Shen C, Gan Y, Chen C, et\u00a0al (2024) Decouple content and motion for conditional image-to-video generation. In: Proceedings of the AAAI conference on artificial intelligence, pp 4757\u20134765","DOI":"10.1609\/aaai.v38i5.28277"},{"key":"11331_CR186","doi-asserted-by":"crossref","unstructured":"Shen L, Li X, Sun H, et\u00a0al (2023) Make-it-4d: Synthesizing a consistent long-term dynamic scene video from a single image. In: Proceedings of the 31st ACM international conference on multimedia, pp 8167\u20138175","DOI":"10.1145\/3581783.3612033"},{"key":"11331_CR187","doi-asserted-by":"crossref","unstructured":"Shi F, Gu J, Xu H, et\u00a0al (2024) Bivdiff: A training-free framework for general-purpose video synthesis via bridging image and video diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7393\u20137402","DOI":"10.1109\/CVPR52733.2024.00706"},{"key":"11331_CR188","doi-asserted-by":"crossref","unstructured":"Shi X, Huang Z, Wang FY, et\u00a0al (2024) Motion-i2v: Consistent and controllable image-to-video generation with explicit motion modeling. arXiv preprint arXiv:2401.15977","DOI":"10.1145\/3641519.3657497"},{"key":"11331_CR189","unstructured":"Siarohin A, et\u00a0al. (2019) First order motion model for image animation. In: NeurIPS"},{"key":"11331_CR190","unstructured":"Singer U, Polyak A, Hayes T, et\u00a0al (2022) Make-a-video: Text-to-video generation without text-video data. arXiv preprint arXiv:2209.14792"},{"key":"11331_CR191","doi-asserted-by":"crossref","unstructured":"Skorokhodov I, Menapace W, Siarohin A, et\u00a0al (2024) Hierarchical patch diffusion models for high-resolution video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7569\u20137579","DOI":"10.1109\/CVPR52733.2024.00723"},{"issue":"6","key":"11331_CR192","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/s10462-024-10800-8","volume":"57","author":"W Song","year":"2024","unstructured":"Song W, Ma W, Zhang M et al (2024) Lightweight diffusion models: a survey. Artif Intell Rev 57(6):161. https:\/\/doi.org\/10.1007\/s10462-024-10800-8","journal-title":"Artif Intell Rev"},{"key":"11331_CR193","unstructured":"Song K, Hou T, He Z, et\u00a0al (2024) Directorllm for human-centric video generation. arXiv preprint arXiv:2412.14484https:\/\/arxiv.org\/abs\/2412.14484"},{"key":"11331_CR194","doi-asserted-by":"publisher","unstructured":"Song J, Meng C, Ermon S (2020b) Denoising diffusion implicit models. In: International Conference on Learning Representations, https:\/\/doi.org\/10.48550\/arXiv.2010.02502","DOI":"10.48550\/arXiv.2010.02502"},{"key":"11331_CR195","doi-asserted-by":"publisher","unstructured":"Song Y, Sohl-Dickstein J, Kingma DP, et\u00a0al (2020a) Score-based generative modeling through stochastic differential equations. In: Advances in Neural Information Processing Systems, pp 12438\u201312450, https:\/\/doi.org\/10.48550\/arXiv.2011.13456","DOI":"10.48550\/arXiv.2011.13456"},{"key":"11331_CR196","unstructured":"Soomro K, Zamir AR, Shah M (2012) Ucf101: A dataset of 101 human actions classes from videos in the wild. arXiv preprint arXiv:1212.0402"},{"key":"11331_CR197","unstructured":"Srivastava N, et\u00a0al. (2015) Unsupervised learning of video representations using lstms. In: ICML"},{"key":"11331_CR198","doi-asserted-by":"crossref","unstructured":"Su S, Liu J, Gao L, et\u00a0al (2024) F$$^3$$-pruning: A training-free and generalized pruning strategy towards faster and finer text-to-video synthesis. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp 4961\u20134969","DOI":"10.1609\/aaai.v38i5.28300"},{"key":"11331_CR199","unstructured":"Sun J, Li M, Chen Z, et\u00a0al (2024) Neurocine: Decoding vivid video sequences from human brain activties. arXiv preprint arXiv:2402.01590"},{"key":"11331_CR200","first-page":"16083","volume":"36","author":"Z Tang","year":"2023","unstructured":"Tang Z, Yang Z, Zhu C et al (2023) Any-to-any generation via composable diffusion. Adv Neural Inf Process Syst 36:16083\u201316099","journal-title":"Adv Neural Inf Process Syst"},{"key":"11331_CR201","unstructured":"Tan Z, Yang X, Liu S, et\u00a0al (2024) Video-infinity: Distributed long video generation. arXiv preprint arXiv:2406.16260"},{"key":"11331_CR202","first-page":"244","volume-title":"European conference on computer vision","author":"L Tian","year":"2024","unstructured":"Tian L, Wang Q, Zhang B et al (2024) Emo: emote portrait alive generating expressive portrait videos with audio2video diffusion model under weak conditions. European conference on computer vision. Springer, Cham, pp 244\u2013260"},{"key":"11331_CR203","unstructured":"Tian S, Xu J, Tang H, et\u00a0al (2021) Aesthetic-driven audiovisual generation with adversarial training. In: ACM MM"},{"key":"11331_CR204","unstructured":"Unterthiner T, van Steenkiste S, Esser P, et\u00a0al (2019) Fvd: A new metric for video generation. arXiv preprint arXiv:1812.01717"},{"key":"11331_CR205","first-page":"23371","volume-title":"Advances in Neural Information Processing Systems","author":"V Voleti","year":"2022","unstructured":"Voleti V, Jolicoeur-Martineau A, Pal C (2022) Mcvd - masked conditional video diffusion for prediction, generation, and interpolation. In: Koyejo S, Mohamed S, Agarwal A et al (eds) Advances in Neural Information Processing Systems, vol 35. Curran Associates Inc, New York, pp 23371\u201323385"},{"key":"11331_CR206","unstructured":"Voleti V, Jolicoeur-Martineau A, Pal C (2022) Mcvd: Masked conditional video diffusion for prediction, generation, and interpolation. arXiv:2205.09853"},{"key":"11331_CR207","first-page":"7068349","volume":"1","author":"A Voulodimos","year":"2018","unstructured":"Voulodimos A, Doulamis N, Doulamis A et al (2018) Deep learning for computer vision: a brief review. Comput Intell Neurosci 1:7068349","journal-title":"Comput Intell Neurosci"},{"key":"11331_CR208","unstructured":"Walke H, Black K, Lee A, et\u00a0al (2024) Bridgedata v2: A dataset for robot learning at scale. arXiv:2308.12952"},{"key":"11331_CR209","unstructured":"Wang FY, Chen W, Song G, et\u00a0al (2023) Gen-l-video: Multi-text to long video generation via temporal co-denoising. arXiv preprint arXiv:2305.18264"},{"key":"11331_CR210","doi-asserted-by":"crossref","unstructured":"Wang FY, Huang Z, Bian W, et\u00a0al (2024) Animatelcm: computation-efficient personalized style video generation without personalized video data. arXiv:2402.00769","DOI":"10.1145\/3681758.3698013"},{"issue":"4","key":"11331_CR211","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"key":"11331_CR212","doi-asserted-by":"crossref","unstructured":"Wang Y, Bao J, Weng W, et\u00a0al (2024) Microcinema: a divide-and-conquer approach for text-to-video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 8414\u20138424","DOI":"10.1109\/CVPR52733.2024.00804"},{"key":"11331_CR213","unstructured":"Wang L, Boddeti V, Lim S (2024) Action reimagined: Text-to-pose video editing for dynamic human actions. arXiv preprint arXiv:2403.07198"},{"key":"11331_CR214","unstructured":"Wang Y, Chen X, Ma X, et\u00a0al (2023) Lavie: High-quality video generation with cascaded latent diffusion models. arXiv preprint arXiv:2309.15103"},{"key":"11331_CR215","first-page":"1","volume":"10","author":"Y Wang","year":"2024","unstructured":"Wang Y, Chen X, Ma X et al (2024) Lavie: high-quality video generation with cascaded latent diffusion models. Int J Comput Vision 10:1\u201320","journal-title":"Int J Comput Vision"},{"key":"11331_CR216","unstructured":"Wang C, Gu J, Hu P, et\u00a0al (2024a) Easycontrol: Transfer controlnet to video diffusion for controllable generation and interpolation. arXiv preprint arXiv:2408.13005"},{"key":"11331_CR217","doi-asserted-by":"crossref","unstructured":"Wang C, Gu J, Hu P, et\u00a0al (2025) Dreamvideo: high-fidelity image-to-video generation with image retention and text guidance. In: ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp 1\u20135","DOI":"10.1109\/ICASSP49660.2025.10887583"},{"key":"11331_CR218","unstructured":"Wang Y, He Y, Li Y, et\u00a0al (2024) Internvid: A large-scale video-text dataset for multimodal understanding and generation. arXiv:2307.06942"},{"key":"11331_CR219","unstructured":"Wang Z, Lan Y, Zhou S, et\u00a0al (2024) Objctrl-2.5 d: training-free object control with camera poses. arXiv preprint arXiv:2412.07721"},{"key":"11331_CR220","unstructured":"Wang X, Li X, Chen Z (2024) Cono: Consistency noise injection for tuning-free long video diffusion. arXiv preprint arXiv:2406.05082"},{"key":"11331_CR221","doi-asserted-by":"crossref","unstructured":"Wang T, Li L, Lin K, et\u00a0al (2024) Disco: disentangled control for realistic human dance generation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9326\u20139336","DOI":"10.1109\/CVPR52733.2024.00891"},{"key":"11331_CR222","unstructured":"Wang W, Liu J, Lin Z, et\u00a0al (2024) Magicvideo-v2: Multi-stage high-aesthetic video generation. arXiv:2401.04468"},{"key":"11331_CR223","unstructured":"Wang Z, Li Y, Zeng Y, et\u00a0al (2024) Humanvid: Demystifying training data for camera-controllable human image animation. In: The Thirty-eighth Conference on Neural Information Processing Systems Datasets and Benchmarks Track"},{"key":"11331_CR224","unstructured":"Wang Z, Li A, Zhu L, et\u00a0al (2024) Customvideo: Customizing text-to-video generation with multiple subjects. arXiv:2401.09962"},{"key":"11331_CR225","doi-asserted-by":"crossref","unstructured":"Wang H, Ouyang H, Wang Q, et\u00a0al (2024) Levitor: 3d trajectory oriented image-to-video synthesis. arXiv preprint arXiv:2412.15214","DOI":"10.1109\/CVPR52734.2025.01165"},{"key":"11331_CR226","doi-asserted-by":"crossref","unstructured":"Wang Q, Shi Y, Ou J, et\u00a0al (2024) Koala-36m: A large-scale video dataset improving consistency between fine-grained conditions and video content. arXiv:2410.08260","DOI":"10.1109\/CVPR52734.2025.00789"},{"key":"11331_CR227","doi-asserted-by":"crossref","unstructured":"Wang Z, Wang L, Zhao Z, et\u00a0al (2024) Gpt4video: A unified multimodal large language model for lnstruction-followed understanding and safety-aware generation. arXiv:2311.16511","DOI":"10.1145\/3664647.3681464"},{"key":"11331_CR228","unstructured":"Wang W, Wang Q, Zheng K, et\u00a0al (2024b) Framer: Interactive frame interpolation. arXiv preprint arXiv:2410.18978"},{"key":"11331_CR229","unstructured":"Wang W, Yang Y (2025) Videoufo: A million-scale user-focused dataset for text-to-video generation. arXiv:2503.01739"},{"key":"11331_CR230","doi-asserted-by":"crossref","unstructured":"Wang W, Yang H, Tuo Z, et\u00a0al (2025) Swap attention in spatiotemporal diffusions for text-to-video generation. International Journal of Computer Vision pp 1\u201319","DOI":"10.1007\/s11263-025-02349-y"},{"key":"11331_CR231","unstructured":"Wang J, Yuan H, Chen D, et\u00a0al (2023) Modelscope text-to-video technical report. arXiv preprint arXiv:2308.06571"},{"key":"11331_CR232","doi-asserted-by":"crossref","unstructured":"Wang Z, Yuan Z, Wang X, et\u00a0al (2024) Motionctrl: A unified and flexible motion controller for video generation. In: ACM SIGGRAPH 2024 Conference Papers, pp 1\u201311","DOI":"10.1145\/3641519.3657518"},{"key":"11331_CR233","unstructured":"Wang X, Yuan H, Zhang S, et\u00a0al (2023) Videocomposer: Compositional video synthesis with motion controllability. arXiv:2306.02018"},{"key":"11331_CR234","doi-asserted-by":"crossref","unstructured":"Wang X, Zhang S, Yuan H, et\u00a0al (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, pp 6572\u20136582","DOI":"10.1109\/CVPR52733.2024.00628"},{"key":"11331_CR235","unstructured":"Wang J, Zhang Y, Zou J, et\u00a0al (2024) Boximator: Generating rich and controllable motions for video synthesis. arXiv preprint arXiv:2402.01566"},{"key":"11331_CR236","doi-asserted-by":"crossref","unstructured":"Wang C, Zheng Z, Yu T, et\u00a0al (2024) Diffperformer: Iterative learning of consistent latent guidance for diffusion-based human video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 6169\u20136179","DOI":"10.1109\/CVPR52733.2024.00590"},{"key":"11331_CR237","unstructured":"Wang X, Zhu Z, Huang G, et\u00a0al (2024) Worlddreamer: Towards general world models for video generation via predicting masked tokens. arXiv:2401.09985"},{"key":"11331_CR238","doi-asserted-by":"crossref","unstructured":"Weng W, Feng R, Wang Y, 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, pp 7395\u20137405","DOI":"10.1109\/CVPRW63382.2024.00735"},{"key":"11331_CR239","doi-asserted-by":"crossref","unstructured":"Wen Y, Zhao Y, Liu Y, et\u00a0al (2023) Panacea: panoramic and controllable video generation for autonomous driving. arXiv:2311.16813","DOI":"10.1109\/CVPR52733.2024.00659"},{"key":"11331_CR240","doi-asserted-by":"crossref","unstructured":"Wu JZ, Ge Y, Wang X, et\u00a0al (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, pp 7623\u20137633","DOI":"10.1109\/ICCV51070.2023.00701"},{"key":"11331_CR241","unstructured":"Wu S, Fei H, Qu L, et\u00a0al (2024) Next-gpt: Any-to-any multimodal llm. In: Forty-first International Conference on Machine Learning"},{"key":"11331_CR242","unstructured":"Wu J, Gan W, Chen Z, et\u00a0al (2023) AI-Generated Content (AIGC): A survey. arXiv preprint arXiv:2304.06632arXiv:2304.06632"},{"key":"11331_CR243","unstructured":"Wu C, Liang J, Hu X, et\u00a0al (2022) Nuwa-infinity: Autoregressive over autoregressive generation for infinite visual synthesis. arXiv preprint arXiv:2207.09814"},{"key":"11331_CR244","unstructured":"Wu B, Lim J, Zhang H, et\u00a0al (2016) Deep multiple instance learning for video classification and anomaly detection. In: BMVC"},{"key":"11331_CR245","doi-asserted-by":"crossref","unstructured":"Wu J, Li X, Si C, et\u00a0al (2024) Towards language-driven video inpainting via multimodal large language models. arXiv preprint arXiv:2401.10226","DOI":"10.1109\/CVPR52733.2024.01188"},{"key":"11331_CR246","doi-asserted-by":"crossref","unstructured":"Wu W, Liu M, Zhu Z, et\u00a0al (2025) Moviebench: a hierarchical movie level dataset for long video generation. arXiv:2411.15262","DOI":"10.1109\/CVPR52734.2025.02699"},{"key":"11331_CR247","doi-asserted-by":"crossref","unstructured":"Wu Z, Siarohin A, Menapace W, et\u00a0al (2025) Mind the time: temporally-controlled multi-event video generation. arXiv:2412.05263","DOI":"10.1109\/CVPR52734.2025.02234"},{"key":"11331_CR248","first-page":"378","volume-title":"European conference on computer vision","author":"T Wu","year":"2024","unstructured":"Wu T, Si C, Jiang Y et al (2024) Freeinit: bridging initialization gap in video diffusion models. European conference on computer vision. Springer, Cham, pp 378\u2013394"},{"key":"11331_CR249","doi-asserted-by":"crossref","unstructured":"Wu W, Yang W, Bao H, et\u00a0al (2022) Nuwa: Visual synthesis with neural visual world architectures. In: ICLR","DOI":"10.1007\/978-3-031-19787-1_41"},{"key":"11331_CR250","unstructured":"Xia T, Chen X, Xu S (2024) Unictrl: Improving the spatiotemporal consistency of text-to-video diffusion models via training-free unified attention control. arXiv:2403.02332"},{"key":"11331_CR251","unstructured":"Xiang J, Huang R, Zhang J, et\u00a0al (2023) Versvideo: Leveraging enhanced temporal diffusion models for versatile video generation. In: The twelfth international conference on learning representations"},{"key":"11331_CR252","doi-asserted-by":"crossref","unstructured":"Xie Y, Xu H, Song G, et\u00a0al (2024) X-portrait: Expressive portrait animation with hierarchical motion attention. In: ACM SIGGRAPH 2024 Conference Papers, pp 1\u201311","DOI":"10.1145\/3641519.3657459"},{"issue":"2","key":"11331_CR253","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3696415","volume":"57","author":"Z Xing","year":"2024","unstructured":"Xing Z, Feng Q, Chen H et al (2024) A survey on video diffusion models. ACM Comput Surv 57(2):1\u201342. https:\/\/doi.org\/10.1145\/3696415","journal-title":"ACM Comput Surv"},{"key":"11331_CR254","doi-asserted-by":"crossref","unstructured":"Xing Z, Dai Q, Hu H, et\u00a0al (2024) Simda: Simple diffusion adapter for efficient video generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7827\u20137839","DOI":"10.1109\/CVPR52733.2024.00748"},{"key":"11331_CR255","unstructured":"Xing Z, Dai Q, Weng Z, et\u00a0al (2024) Aid: Adapting image2video diffusion models for instruction-guided video prediction. arXiv preprint arXiv:2406.06465"},{"key":"11331_CR256","unstructured":"Xing Z, Dai Q, Zhang Z, et\u00a0al (2023) Vidiff: Translating videos via multi-modal instructions with diffusion models. arXiv preprint arXiv:2311.18837"},{"key":"11331_CR257","doi-asserted-by":"crossref","unstructured":"Xing Y, He Y, Tian Z, et\u00a0al (2024) Seeing and hearing: Open-domain visual-audio generation with diffusion latent aligners. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7151\u20137161","DOI":"10.1109\/CVPR52733.2024.00683"},{"key":"11331_CR258","doi-asserted-by":"crossref","unstructured":"Xing J, Xia M, Liu Y, et\u00a0al (2024) Make-your-video: Customized video generation using textual and structural guidance. IEEE transactions on visualization and computer graphics","DOI":"10.1109\/TVCG.2024.3365804"},{"key":"11331_CR259","first-page":"399","volume-title":"European conference on computer vision","author":"J Xing","year":"2024","unstructured":"Xing J, Xia M, Zhang Y et al (2024) Dynamicrafter: animating open-domain images with video diffusion priors. European conference on computer vision. Springer, Cham, pp 399\u2013417"},{"key":"11331_CR260","doi-asserted-by":"crossref","unstructured":"Xiong W, Luo W, Ma L, et\u00a0al (2018) Learning to generate time-lapse videos using multi-stage dynamic generative adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 2364\u20132373","DOI":"10.1109\/CVPR.2018.00251"},{"key":"11331_CR261","unstructured":"Xiong T, Wang Y, Zhou D, et\u00a0al (2024) Lvd-2m: A long-take video dataset with temporally dense captions. arXiv:2410.10816"},{"key":"11331_CR262","unstructured":"Xuanyuan M, Wang Y, Guo H, et\u00a0al (2024) Context-aware talking face video generation. arXiv preprint arXiv:2402.18092"},{"key":"11331_CR263","doi-asserted-by":"crossref","unstructured":"Xu M, Du H, Niyato D, et\u00a0al (2024) Unleashing the power of edge-cloud generative ai in mobile networks: a survey of AIGC services. IEEE Communications Surveys & Tutorials arXiv:2303.16129","DOI":"10.1109\/COMST.2024.3353265"},{"key":"11331_CR264","unstructured":"Xu M, Li H, Su Q, et\u00a0al (2024) Hallo: Hierarchical audio-driven visual synthesis for portrait image animation. arXiv preprint arXiv:2406.08801"},{"key":"11331_CR265","doi-asserted-by":"crossref","unstructured":"Xu J, Mei T, Yao T, et\u00a0al (2016) Msr-vtt: A large video description dataset for bridging video and language. In: CVPR","DOI":"10.1109\/CVPR.2016.571"},{"key":"11331_CR266","unstructured":"Xu Z, Wei K, Yang X, et\u00a0al (2024a) Do you guys want to dance: Zero-shot compositional human dance generation with multiple persons. arXiv preprint arXiv:2401.13363"},{"key":"11331_CR267","unstructured":"Xu H, Ye Q, Wu X, et\u00a0al (2023) Youku-mplug: a 10 million large-scale chinese video-language dataset for pre-training and benchmarks. arXiv:2306.04362"},{"key":"11331_CR268","doi-asserted-by":"crossref","unstructured":"Xu Z, Zhang J, Liew JH, et\u00a0al (2024b) Magicanimate: temporally consistent human image animation using diffusion model. In: Proceedings of the IEEE\/CVF Conference on computer vision and pattern recognition, pp 1481\u20131490","DOI":"10.1109\/CVPR52733.2024.00147"},{"key":"11331_CR269","doi-asserted-by":"crossref","unstructured":"Yan X, Cai Y, Wang Q, et\u00a0al (2024) Long video diffusion generation with segmented cross-attention and content-rich video data curation. arXiv preprint arXiv:2412.01316","DOI":"10.1109\/CVPR52734.2025.00303"},{"issue":"4","key":"11331_CR270","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3626235","volume":"56","author":"L Yang","year":"2023","unstructured":"Yang L, Zhang Z, Song Y et al (2023) Diffusion models: a comprehensive survey of methods and applications. ACM Comput Surv 56(4):1\u201339 arXiv:2209.00796","journal-title":"ACM Comput Surv"},{"key":"11331_CR271","unstructured":"Yang M, Du Y, Dai B, et\u00a0al (2023) Probabilistic adaptation of text-to-video models. arXiv preprint arXiv:2306.01872"},{"key":"11331_CR272","doi-asserted-by":"crossref","unstructured":"Yang R, Gamper H, Braun S (2024) Cmmd: Contrastive multi-modal diffusion for video-audio conditional modeling. arXiv:2312.05412","DOI":"10.1007\/978-3-031-93806-1_16"},{"key":"11331_CR273","unstructured":"Yang X, He C, Ma J, et\u00a0al (2023) Motion-guided latent diffusion for temporally consistent real-world video super-resolution. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR)"},{"key":"11331_CR274","doi-asserted-by":"crossref","unstructured":"Yang S, Hou L, Huang H, et\u00a0al (2024) Direct-a-video: Customized video generation with user-directed camera movement and object motion. In: ACM SIGGRAPH 2024 Conference Papers, pp 1\u201312","DOI":"10.1145\/3641519.3657481"},{"key":"11331_CR275","unstructured":"Yang Y, Jiao L, Liu X, et\u00a0al (2022) Transformers meet visual learning understanding: a comprehensive review. arXiv preprint arXiv:2203.12944"},{"key":"11331_CR276","doi-asserted-by":"crossref","unstructured":"Yang S, Li H, Wu J, et\u00a0al (2024) Megactor: Unlocking flexible mixed-modal control in portrait animation with diffusion transformer. arXiv preprint arXiv:2408.14975","DOI":"10.1609\/aaai.v39i9.33002"},{"key":"11331_CR277","unstructured":"Yang Q, Mao B, Wang Z, et\u00a0al (2024) Draw an audio: Leveraging multi-instruction for video-to-audio synthesis. arXiv preprint arXiv:2409.06135"},{"key":"11331_CR278","unstructured":"Yang T, Shi Y, Huang Y, et\u00a0al (2024) Factorized-dreamer: training a high-quality video generator with limited and low-quality data. arXiv preprint arXiv:2408.10119"},{"key":"11331_CR279","doi-asserted-by":"crossref","unstructured":"Yang R, Srivastava P, Mandt S (2022) Diffusion probabilistic modeling for video generation. arXiv:2203.09481","DOI":"10.3390\/e25101469"},{"key":"11331_CR280","unstructured":"Yang Z, Teng J, Zheng W, et\u00a0al (2024) Cogvideox: Text-to-video diffusion models with an expert transformer. arXiv preprint arXiv:2408.06072"},{"key":"11331_CR281","doi-asserted-by":"crossref","unstructured":"Yang S, Zhang L, Liu Y, et\u00a0al (2023) Video diffusion models with local-global context guidance. arXiv preprint arXiv:2306.02562","DOI":"10.24963\/ijcai.2023\/182"},{"key":"11331_CR282","unstructured":"Yan W, Zhang Y, Abbeel P, et\u00a0al (2021) Videogpt: Video generation using vq-vae and transformers. arXiv preprint arXiv:2104.10157"},{"key":"11331_CR283","unstructured":"Yan D, Zhang W, Zhang L, et\u00a0al (2024) Animated stickers: Bringing stickers to life with video diffusion. arXiv preprint arXiv:2402.06088"},{"key":"11331_CR284","doi-asserted-by":"crossref","unstructured":"Yariv G, Gat I, Benaim S, et\u00a0al (2023) Diverse and aligned audio-to-video generation via text-to-video model adaptation. arXiv:2309.16429","DOI":"10.1609\/aaai.v38i7.28486"},{"key":"11331_CR285","doi-asserted-by":"crossref","unstructured":"Ye X, Bilodeau GA (2024) Stdiff: Spatio-temporal diffusion for continuous stochastic video prediction. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp 6666\u20136674","DOI":"10.1609\/aaai.v38i7.28489"},{"key":"11331_CR286","unstructured":"Yin S, Wu C, Liang J, et\u00a0al (2023) Dragnuwa: Fine-grained control in video generation by integrating text, image, and trajectory. arXiv:2308.08089"},{"key":"11331_CR287","doi-asserted-by":"crossref","unstructured":"Yin S, Wu C, Yang H, et\u00a0al (2023) Nuwa-xl: Diffusion over diffusion for extremely long video generation. arXiv preprint arXiv:2303.12346","DOI":"10.18653\/v1\/2023.acl-long.73"},{"key":"11331_CR288","doi-asserted-by":"publisher","unstructured":"Yin S, Wu C, Yang H, et\u00a0al (2023) Nuwa-xl: Diffusion over diffusion for extremely long video generation. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, pp 1309\u20131320, https:\/\/doi.org\/10.18653\/v1\/2023.acl-long.73, URL https:\/\/aclanthology.org\/2023.acl-long.73\/","DOI":"10.18653\/v1\/2023.acl-long.73"},{"key":"11331_CR289","doi-asserted-by":"crossref","unstructured":"Yuan X, Baek J, Xu K, et\u00a0al (2024) Inflation with diffusion: Efficient temporal adaptation for text-to-video super-resolution. In: Proceedings of the IEEE\/CVF winter conference on applications of computer vision (WACV)","DOI":"10.1109\/WACVW60836.2024.00059"},{"key":"11331_CR290","doi-asserted-by":"crossref","unstructured":"Yuan S, Huang J, He X, et\u00a0al (2024) Identity-preserving text-to-video generation by frequency decomposition. arXiv preprint arXiv:2411.17440","DOI":"10.32388\/TZIID6"},{"key":"11331_CR291","unstructured":"Yuan S, Huang J, Xu Y, et\u00a0al (2024) Chronomagic-bench: a benchmark for metamorphic evaluation of text-to-time-lapse video generation. arXiv:2406.18522"},{"key":"11331_CR292","unstructured":"Yuan Z, Liu Y, Cao Y, et\u00a0al (2024) Mora: enabling generalist video generation via a multi-agent framework. arXiv preprint arXiv:2403.13248"},{"key":"11331_CR293","unstructured":"Yu S, Nie W, Huang DA, et\u00a0al (2024) Efficient video diffusion models via content-frame motion-latent decomposition. In: International conference on learning representations, https:\/\/openreview.net\/forum?id=dQVtTdsvZH"},{"key":"11331_CR294","doi-asserted-by":"crossref","unstructured":"Yu S, Sohn K, Kim S, et\u00a0al (2023) Video probabilistic diffusion models in projected latent space. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 18456\u201318466","DOI":"10.1109\/CVPR52729.2023.01770"},{"key":"11331_CR295","doi-asserted-by":"crossref","unstructured":"Yu J, Zhu H, Jiang L, et\u00a0al (2023) Celebv-text: A large-scale facial text-video dataset. arXiv:2303.14717","DOI":"10.1109\/CVPR52729.2023.01422"},{"key":"11331_CR296","unstructured":"Zaken EB, Ravfogel S, Goldberg Y (2021) Bitfit: simple parameter-efficient fine-tuning for transformer-based masked language-models. arXiv preprint arXiv:2106.10199"},{"key":"11331_CR297","unstructured":"Zellers R (2022) Advancing high-resolution video-language representation with large-scale video transcriptions. In: CVPR"},{"key":"11331_CR298","doi-asserted-by":"crossref","unstructured":"Zeng Y, Wei G, Zheng J, et\u00a0al (2024) Make pixels dance: High-dynamic video generation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8850\u20138860","DOI":"10.1109\/CVPR52733.2024.00845"},{"key":"11331_CR299","unstructured":"Zhang DJ, Li D, Le H, et\u00a0al (2024) Moonshot: towards controllable video generation and editing with multimodal conditions. arXiv:2401.01827"},{"key":"11331_CR300","doi-asserted-by":"crossref","unstructured":"Zhang DJ, Paiss R, Zada S, et\u00a0al (2024) Recapture: generative video camera controls for user-provided videos using masked video fine-tuning. arXiv preprint arXiv:2411.05003","DOI":"10.1109\/CVPR52734.2025.00197"},{"key":"11331_CR301","first-page":"1","volume":"10","author":"DJ Zhang","year":"2024","unstructured":"Zhang DJ, Wu JZ, Liu JW et al (2024) Show-1: marrying pixel and latent diffusion models for text-to-video generation. Int J Comput Vision 10:1\u201315","journal-title":"Int J Comput Vision"},{"key":"11331_CR302","unstructured":"Zhang R, Chen Y, Liu Y, et\u00a0al (2024) Tvg: A training-free transition video generation method with diffusion models. arXiv:2408.13413"},{"key":"11331_CR303","unstructured":"Zhang Y, Gu J, Wang LW, et\u00a0al (2024) Mimicmotion: High-quality human motion video generation with confidence-aware pose guidance. arXiv preprint arXiv:2406.19680"},{"key":"11331_CR304","unstructured":"Zhang Y, Kang Y, Zhang Z, et\u00a0al (2024) Interactivevideo: User-centric controllable video generation with synergistic multimodal instructions. arXiv preprint arXiv:2402.03040"},{"key":"11331_CR305","doi-asserted-by":"crossref","unstructured":"Zhang Z, Liao J, Li M, et\u00a0al (2024) Tora: Trajectory-oriented diffusion transformer for video generation. arXiv preprint arXiv:2407.21705","DOI":"10.1109\/CVPR52734.2025.00198"},{"key":"11331_CR306","unstructured":"Zhang S, Wang J, Zhang Y, et\u00a0al (2023) I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models. arXiv preprint arXiv:2311.04145"},{"key":"11331_CR307","unstructured":"Zhang Y, Wei Y, Lin X, et\u00a0al (2024) Videoelevator: Elevating video generation quality with versatile text-to-image diffusion models. https:\/\/arxiv.org\/abs\/2403.05438, arXiv:2403.05438"},{"key":"11331_CR308","doi-asserted-by":"crossref","unstructured":"Zhang Z, Wu B, Wang X, et\u00a0al (2023) Avid: Any-length video inpainting with diffusion model. arXiv preprint arXiv:2312.03816","DOI":"10.1109\/CVPR52733.2024.00684"},{"key":"11331_CR309","unstructured":"Zhang H, Wu Z, Xing Z, et\u00a0al (2023) Adadiff: Adaptive step selection for fast diffusion. arXiv preprint arXiv:2311.14768"},{"key":"11331_CR310","unstructured":"Zhang C, Zhang C, Zheng S, et\u00a0al (2023) A survey on audio diffusion models: Text to speech synthesis and enhancement in generative ai. arXiv preprint arXiv:2303.13336"},{"key":"11331_CR311","unstructured":"Zhao L, Feng L, Ge D, et\u00a0al (2025) Uniform: A unified diffusion transformer for audio-video generation. arXiv preprint arXiv:2502.03897"},{"key":"11331_CR312","doi-asserted-by":"crossref","unstructured":"Zhao R, Gu Y, Wu JZ, et\u00a0al (2024a) Motiondirector: motion customization of text-to-video diffusion models. In: European Conference on Computer Vision, Springer, pp 273\u2013290","DOI":"10.1007\/978-3-031-72992-8_16"},{"key":"11331_CR313","doi-asserted-by":"crossref","unstructured":"Zhao H, Lu T, Gu J, et\u00a0al (2024b) Magdiff: Multi-alignment diffusion for high-fidelity video generation and editing. In: European Conference on Computer Vision, Springer, pp 205\u2013221","DOI":"10.1007\/978-3-031-72649-1_12"},{"key":"11331_CR314","unstructured":"Zhao M, Zhu H, Xiang C, et\u00a0al (2024) Identifying and solving conditional image leakage in image-to-video diffusion model. arXiv preprint arXiv:2406.15735"},{"key":"11331_CR315","unstructured":"Zheng G, Li T, Jiang R, et\u00a0al (2024) Cami2v: Camera-controlled image-to-video diffusion model. arXiv preprint arXiv:2410.15957"},{"key":"11331_CR316","unstructured":"Zhou Q, Li R, Guo S, et\u00a0al (2022) Cadm: Codec-aware diffusion modeling for neural-enhanced video streaming. arXiv preprint arXiv:2211.08428"},{"key":"11331_CR317","unstructured":"Zhou D, Wang W, Yan H, et\u00a0al (2022) Magicvideo: Efficient video generation with latent diffusion models. arXiv preprint arXiv:2211.11018"},{"key":"11331_CR318","doi-asserted-by":"crossref","unstructured":"Zhou S, Yang P, Wang J, et\u00a0al (2023) Upscale-a-video: Temporal-consistent diffusion model for real-world video super-resolution. arXiv preprint arXiv:2312.06640","DOI":"10.1109\/CVPR52733.2024.00245"},{"key":"11331_CR319","doi-asserted-by":"crossref","unstructured":"Zhuang S, Li K, Chen X, et\u00a0al (2024) Vlogger: Make your dream a vlog. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 8806\u20138817","DOI":"10.1109\/CVPR52733.2024.00841"},{"key":"11331_CR320","doi-asserted-by":"crossref","unstructured":"Zhu S, Chen JL, Dai Z, et\u00a0al (2024) Champ: Controllable and consistent human image animation with 3d parametric guidance. In: European Conference on Computer Vision, Springer, pp 145\u2013162","DOI":"10.1007\/978-3-031-73001-6_9"},{"key":"11331_CR321","doi-asserted-by":"crossref","unstructured":"Zhu J, Yang H, He H, et\u00a0al (2023) Moviefactory: Automatic movie creation from text using large generative models for language and images. In: Proceedings of the 31st ACM International Conference on Multimedia, pp 9313\u20139319","DOI":"10.1145\/3581783.3612707"},{"key":"11331_CR322","unstructured":"Zi B, Ruan P, Chen M, et\u00a0al (2025) Se\u00f1orita-2m: A high-quality instruction-based dataset for general video editing by video specialists. arXiv:2502.06734"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11331-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-025-11331-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11331-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T01:49:08Z","timestamp":1761356948000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-025-11331-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,20]]},"references-count":322,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["11331"],"URL":"https:\/\/doi.org\/10.1007\/s10462-025-11331-6","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,20]]},"assertion":[{"value":"15 July 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 August 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"338"}}