DragVideo: Interactive Drag-style Video Editing
Authors: name: Yufan Deng, name: Ruida Wang, name: Yuhao Zhang, name: Yu-Wing Tai, name: Chi-Keung Tang

Editing visual content on videos remains a formidable challenge with two main
issues: 1) direct and easy user control to produce 2) natural editing results
without unsightly distortion and artifacts after changing shape, expression and
layout. Inspired by DragGAN, a recent image-based drag-style editing technique,
we address above issues by proposing DragVideo, where a similar drag-style user
interaction is adopted to edit video content while maintaining temporal
consistency. Empowered by recent diffusion models as in DragDiffusion,
DragVideo contains the novel Drag-on-Video U-Net (DoVe) editing method, which
optimizes diffused video latents generated by video U-Net to achieve the
desired control. Specifically, we use Sample-specific LoRA fine-tuning and
Mutual Self-Attention control to ensure faithful reconstruction of video from
the DoVe method. We also present a series of testing examples for drag-style
video editing and conduct extensive experiments across a wide array of
challenging editing tasks, such as motion editing, skeleton editing, etc,
underscoring DragVideo's versatility and generality. Our codes including the
DragVideo web user interface will be released.