{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T06:07:31Z","timestamp":1784268451851,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,12,10]],"date-time":"2023-12-10T00:00:00Z","timestamp":1702166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,12,10]]},"DOI":"10.1145\/3610548.3618211","type":"proceedings-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T12:28:40Z","timestamp":1702297720000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Adaptive Recurrent Frame Prediction with Learnable Motion Vectors"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5311-8404","authenticated-orcid":false,"given":"Zhizhen","family":"Wu","sequence":"first","affiliation":[{"name":"State Key Lab of CAD&amp;CG, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1193-9564","authenticated-orcid":false,"given":"Chenyu","family":"Zuo","sequence":"additional","affiliation":[{"name":"State Key Lab of CAD&amp;CG, State Key Laboratory of CAD &amp; CG, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3296-7999","authenticated-orcid":false,"given":"Yuchi","family":"Huo","sequence":"additional","affiliation":[{"name":"State Key Lab of CAD&amp;CG, Zhejiang University, China and Zhejiang Lab, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8857-8373","authenticated-orcid":false,"given":"Yazhen","family":"Yuan","sequence":"additional","affiliation":[{"name":"Tencent, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0667-2599","authenticated-orcid":false,"given":"Yifan","family":"Peng","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0778-6171","authenticated-orcid":false,"given":"Guiyang","family":"Pu","sequence":"additional","affiliation":[{"name":"China Mobile (Hangzhou) Information Technology Co., Ltd, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4267-0347","authenticated-orcid":false,"given":"Rui","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Lab of CAD&amp;CG, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2662-0334","authenticated-orcid":false,"given":"Hujun","family":"Bao","sequence":"additional","affiliation":[{"name":"State Key Lab of CAD&amp;CG, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,12,11]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"AMD. 2022. FidelityFX Super Resolution 2.1. Retrieved 2022 from https:\/\/github.com\/GPUOpen-Effects\/FidelityFX-FSR2"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00382"},{"key":"e_1_3_2_2_3_1","volume-title":"Memc-net: Motion estimation and motion compensation driven neural network for video interpolation and enhancement","author":"Bao Wenbo","year":"2019","unstructured":"Wenbo Bao, Wei-Sheng Lai, Xiaoyun Zhang, Zhiyong Gao, and Ming-Hsuan Yang. 2019b. Memc-net: Motion estimation and motion compensation driven neural network for video interpolation and enhancement. IEEE transactions on pattern analysis and machine intelligence 43, 3 (2019), 933\u2013948."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3478513.3480553"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073601"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.1994.413553"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6634"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6693"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.316"},{"key":"e_1_3_2_2_10_1","unstructured":"Epic Games. 2022. Unreal Engine. Retrieved 2022 from https:\/\/unrealengine.com"},{"key":"e_1_3_2_2_11_1","first-page":"1","article-title":"ExtraNet: real-time extrapolated rendering for low-latency temporal supersampling","volume":"40","author":"Guo Jie","year":"2021","unstructured":"Jie Guo, Xihao Fu, Liqiang Lin, Hengjun Ma, Yanwen Guo, Shiqiu Liu, and Ling-Qi Yan. 2021. ExtraNet: real-time extrapolated rendering for low-latency temporal supersampling. ACM Transactions on Graphics (TOG) 40, 6 (2021), 1\u201316.","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"e_1_3_2_2_12_1","unstructured":"Yu-Xiao Guo Guojun Chen Yue Dong and Xin Tong. 2022. Classifier Guided Temporal Supersampling for Real-time Rendering. (2022)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_15_1","volume-title":"A dynamic multi-scale voxel flow network for video prediction. arXiv preprint arXiv:2303.09875","author":"Hu Xiaotao","year":"2023","unstructured":"Xiaotao Hu, Zhewei Huang, Ailin Huang, Jun Xu, and Shuchang Zhou. 2023. A dynamic multi-scale voxel flow network for video prediction. arXiv preprint arXiv:2303.09875 (2023)."},{"key":"e_1_3_2_2_16_1","volume-title":"FlowFormer: A Transformer Architecture for Optical Flow. ECCV","author":"Huang Zhaoyang","year":"2022","unstructured":"Zhaoyang Huang, Xiaoyu Shi, Chao Zhang, Qiang Wang, Ka\u00a0Chun Cheung, Hongwei Qin, Jifeng Dai, and Hongsheng Li. 2022a. FlowFormer: A Transformer Architecture for Optical Flow. ECCV (2022)."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19781-9_36"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58565-5_11"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00936"},{"key":"e_1_3_2_2_20_1","volume-title":"A lightweight optical flow CNN\u2014Revisiting data fidelity and regularization","author":"Hui Tak-Wai","year":"2020","unstructured":"Tak-Wai Hui, Xiaoou Tang, and Chen\u00a0Change Loy. 2020. A lightweight optical flow CNN\u2014Revisiting data fidelity and regularization. IEEE transactions on pattern analysis and machine intelligence 43, 8 (2020), 2555\u20132569."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00590"},{"key":"e_1_3_2_2_22_1","volume-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Ilg E.","unstructured":"E. Ilg, N. Mayer, T. Saikia, M. Keuper, and T. Brox. 2017. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_2_23_1","unstructured":"Intel. 2022. Intel Xe Super Sampling. https:\/\/www.intel.com\/content\/www\/us\/en\/products\/docs\/arc-discrete-graphics\/xess.html\/"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00938"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00963"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00158"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00201"},{"key":"e_1_3_2_2_28_1","volume-title":"Graphics Interface","author":"Li Zhan","year":"2022","unstructured":"Zhan Li, Carl\u00a0S Marshall, Deepak\u00a0S Vembar, and Feng Liu. 2022. Future Frame Synthesis for Fast Monte Carlo Rendering. In Graphics Interface 2022."},{"key":"e_1_3_2_2_29_1","volume-title":"GPU Technology Conference (GTC).","author":"Liu Edward","year":"2020","unstructured":"Edward Liu. 2020. DLSS 2.0-Image reconstruction for real-time rendering with deep learning. In GPU Technology Conference (GTC)."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.478"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.37"},{"key":"e_1_3_2_2_32_1","unstructured":"NVIDIA. 2022. DLSS 3.0. Retrieved 2022 from https:\/\/www.nvidia.com\/en-us\/geforce\/technologies\/dlss\/"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.291"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_2_35_1","volume-title":"Computer Graphics Forum, Vol.\u00a031","author":"Scherzer Daniel","unstructured":"Daniel Scherzer, Lei Yang, Oliver Mattausch, Diego Nehab, Pedro\u00a0V Sander, Michael Wimmer, and Elmar Eisemann. 2012. Temporal coherence methods in real-time rendering. In Computer Graphics Forum, Vol.\u00a031. Wiley Online Library, 2378\u20132408."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3105762.3105770"},{"key":"e_1_3_2_2_37_1","volume-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting. Advances in neural information processing systems 28","author":"Shi Xingjian","year":"2015","unstructured":"Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo. 2015. Convolutional LSTM network: A machine learning approach for precipitation nowcasting. Advances in neural information processing systems 28 (2015)."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00931"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_24"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7091-6809-7_3"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00795"},{"key":"e_1_3_2_2_42_1","volume-title":"Quadratic video interpolation. Advances in Neural Information Processing Systems 32","author":"Xu Xiangyu","year":"2019","unstructured":"Xiangyu Xu, Li Siyao, Wenxiu Sun, Qian Yin, and Ming-Hsuan Yang. 2019. Quadratic video interpolation. Advances in Neural Information Processing Systems 32 (2019)."},{"key":"e_1_3_2_2_43_1","volume-title":"Computer graphics forum, Vol.\u00a039","author":"Yang Lei","unstructured":"Lei Yang, Shiqiu Liu, and Marco Salvi. 2020. A survey of temporal antialiasing techniques. In Computer graphics forum, Vol.\u00a039. Wiley Online Library, 607\u2013621."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2022.3217305"},{"key":"e_1_3_2_2_45_1","volume-title":"Computer Graphics Forum, Vol.\u00a040","author":"Zeng Zheng","unstructured":"Zheng Zeng, Shiqiu Liu, Jinglei Yang, Lu Wang, and Ling-Qi Yan. 2021. Temporally Reliable Motion Vectors for Real-time Ray Tracing. In Computer Graphics Forum, Vol.\u00a040. Wiley Online Library, 79\u201390."}],"event":{"name":"SA '23: SIGGRAPH Asia 2023","location":"Sydney NSW Australia","acronym":"SA '23","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"]},"container-title":["SIGGRAPH Asia 2023 Conference Papers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3610548.3618211","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3610548.3618211","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T09:36:02Z","timestamp":1755768962000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3610548.3618211"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,10]]},"references-count":45,"alternative-id":["10.1145\/3610548.3618211","10.1145\/3610548"],"URL":"https:\/\/doi.org\/10.1145\/3610548.3618211","relation":{},"subject":[],"published":{"date-parts":[[2023,12,10]]},"assertion":[{"value":"2023-12-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}