arXiv AI
Jul 7

Motion Attribution for Video Generation

arXiv:2601. 08828v2 Announce Type: replace-cross Abstract: Despite the rapid progress of video generation models, the role of data in influencing motion is poorly understood.

By Xindi Wu, Despoina Paschalidou, Jun Gao, Antonio Torralba, Laura Leal-Taix\'e, Olga Russakovsky, Sanja Fidler, Jonathan Lorraine
arXiv Computer Vision
Oct 19

Erase the Mark, Preserve the Motion: Temporally Consistent Removal of Video Watermarks

PoseRegen is a new framework for removing video watermarks while maintaining temporal consistency and motion fidelity. It first applies a shared viewpoint transformation to break watermark patterns, then reconstructs the sequence with a pose‑conditioned video model and Flow Matching supervision to preserve identity and background. The method also includes a Pose‑Conditioned Motion Consistency Adapter to keep body‑part trajectories stable, achieving near‑random watermark bit accuracy and outperforming baselines on motion metrics.

By Yifan Liao, Zhen Sun, Zhicong Huang, Jiaming He, Zongmin Zhang, Xi Ai, Cheng Hong, Xinhu Zheng, Xinlei He