Generative Video Propagation
Shaoteng Liu, Tianyu Wang, Jui-Hsien Wang, Qing Liu, Zhifei Zhang, Joon-Young Lee, Yijun Li, Bei Yu, Zhe Lin, Soo Ye Kim, Jiaya Jia
Abstract
Original Frame #1 Edited Frame #1 Input Video Frames (top) / Propagated by Ours (bottom) (b) Background Replacement (d) Object & Effect Tracking (e) Multiple Edits (a) Object & Effect Removal (c) Object Insertion 1 2 3 3 Figure 1. GenProp. We propose a generative video propagation framework (GenProp), which can seamlessly propagate any first frame edit through the video. GenProp supports a wide range of video applications, including (a) complete object removal with effects such as shadows and reflections, (b) background replacement with realistic effects, (c) object insertion where inserted objects have physically plausible motion (i.e., blueberries falling while spoon goes up), (d) tracking of objects and their associated effects, and (e) multiple edits (outpainting, insertion, removal) at a single inference run.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 8c2bdbbc-3047-47ce-a7ff-5ec59a5702efCited by top-tier papers23
- EditVerse: Unifying Image and Video Editing and Generation with In-Context LearningXuan Ju, Tianyu Wang, Yuqian Zhou, He Zhang et al.ICLR 2026 · 56 citations
- MiniMax-Remover: Taming Bad Noise Helps Video Object RemovalBojia Zi, Weixuan Peng, Xianbiao Qi, Jianan Wang et al.NeurIPS 2025 · 43 citations
- Unified In-Context Video EditingZixuan Ye, Xuanhua He, Quande Liu, Qiulin Wang et al.ICLR 2026 · 37 citations
- Generative Video Motion Editing with 3D Point TracksYao-Chih Lee, Zhoutong Zhang, Jiahui Huang, Jui-Hsien Wang et al.CVPR 2026 · 23 citations
- OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control ConditionsYuanhao Cai, He Zhang, Xi Chen, Jinbo Xing et al.NeurIPS 2025 · 19 citations
Builds on26
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
- Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video GenerationJay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei et al.ICCV 2023 · 1,113 citations
- FateZero: Fusing Attentions for Zero-shot Text-based Video EditingChenyang Qi, Xiaodong Cun, Yong Zhang, Chenyang Lei et al.ICCV 2023 · 510 citations
- Pix2Video: Video Editing using Image DiffusionDuygu Ceylan, Chun-Hao Paul Huang, Niloy J. MitraICCV 2023 · 370 citations
Related papers
- Generative Omnimatte: Learning to Decompose Video into LayersYao-Chih Lee, Erika Lu, Sarah Rumbley, Michal Geyer et al.CVPR 2025
- VideoHandles: Editing 3D Object Compositions in Videos Using Video Generative PriorsJuil Koo, Paul Guerrero, Chun-Hao Paul Huang, Duygu Ceylan et al.CVPR 2025
- FlowVid: Taming Imperfect Optical Flows for Consistent Video-to-Video SynthesisFeng Liang, Bichen Wu, Jialiang Wang, Licheng Yu et al.CVPR 2024
- SketchVideo: Sketch-based Video Generation and EditingFeng-Lin Liu, Hongbo Fu, Xintao Wang, Weicai Ye et al.CVPR 2025
- MetaShadow: Object-Centered Shadow Detection, Removal, and SynthesisTianyu Wang, Jianming Zhang, Haitian Zheng, Zhihong Ding et al.CVPR 2025
