Papers › VideoComposer: Compositional Video Synthesis with Motion Controllability
VideoComposer: Compositional Video Synthesis with Motion Controllability
Xiang Wang, Hangjie Yuan, Shiwei Zhang, Dayou Chen, Jiuniu Wang, Yingya Zhang, Yujun Shen, Deli Zhao, Jingren Zhou
The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis. However, achieving controllable video synthesis remains challenging due to the large variation of temporal dynamics and the requirement of cross-frame temporal consistency. Based on the paradigm of compositional generation, this work presents VideoComposer that allows users to flexibly compose a video with textual conditions, spatial conditions, and more importantly temporal conditions. Specifically, considering the characteristic of video data, we introduce the motion vector from compressed videos as an explicit control signal to provide guidance regarding temporal dynamics. In addition, we develop a Spatio-Temporal Condition encoder (STC-encoder) that serves as a unified interface to effectively incorporate the spatial and temporal relations of sequential inputs, with which the model could make better use of temporal conditions and hence achieve higher inter-frame consistency. Extensive experimental results suggest that VideoComposer is able to control the spatial and temporal patterns simultaneously within a synthesized video in various forms, such as text description, sketch sequence, reference video, or even simply hand-crafted motions. The code and models will be publicly available at https://videocomposer.github.io.
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Code
Syntology Ran 5 of 21 code samples harvested from 2 repositories linked to this paper; 16 have no recorded run. Of those that ran: 3 ran · our draft was wrong; 1 ran · fixture could not drive it; 1 ran with no contract checked.
By repository: community (archive-listed): 20 samples from 2 repositories, 4 ran; 1 identical to code first harvested elsewhere. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.
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Code Syntology ran Syntology
21 samples harvested; 5 ran; 0 honoured the contract we drafted; 16 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Text-to-Video Generation | EvalCrafter Text-to-Video (ECTV) Dataset | ModelScope | Motion Quality | 53.09 | #5 of 5 | Archive leaderboard | report |
| Text-to-Video Generation | EvalCrafter Text-to-Video (ECTV) Dataset | ModelScope | Temporal Consistency | 54.46 | #5 of 5 | Archive leaderboard | report |
| Text-to-Video Generation | EvalCrafter Text-to-Video (ECTV) Dataset | ModelScope | Text-to-Video Alignment | 57.8 | #5 of 5 | Archive leaderboard | report |
| Text-to-Video Generation | EvalCrafter Text-to-Video (ECTV) Dataset | ModelScope | Total Score | 218 | #5 of 5 | Archive leaderboard | report |
| Text-to-Video Generation | EvalCrafter Text-to-Video (ECTV) Dataset | ModelScope | Visual Quality | 52.47 | #5 of 5 | Archive leaderboard | report |
| Text-to-Video Generation | MSR-VTT | VideoComposer | CLIPSIM | 0.2932 | #10 of 18 | Archive leaderboard | report |
| Text-to-Video Generation | MSR-VTT | VideoComposer | FVD | 580 | #10 of 18 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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