V2Edit: Versatile Video Diffusion Editor for Videos and 3D Scenes

• URL: http://arxiv.org/abs/2503.10634v2
• Date: Fri, 14 Mar 2025 23:26:06 GMT
• Title: V2Edit: Versatile Video Diffusion Editor for Videos and 3D Scenes
• Authors: Yanming Zhang, Jun-Kun Chen, Jipeng Lyu, Yu-Xiong Wang,
• Abstract summary: V$2$Edit is a training-free framework for instruction-guided video and 3D scene editing.<n>We introduce a progressive strategy that decomposes complex editing tasks into simpler subtasks.<n>We extend V$2$Edit to 3D scene editing via a "render-edit-reconstruct" process, enabling high-quality, 3D-consistent edits.
• Score: 29.80140472486948
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces V$^2$Edit, a novel training-free framework for instruction-guided video and 3D scene editing. Addressing the critical challenge of balancing original content preservation with editing task fulfillment, our approach employs a progressive strategy that decomposes complex editing tasks into a sequence of simpler subtasks. Each subtask is controlled through three key synergistic mechanisms: the initial noise, noise added at each denoising step, and cross-attention maps between text prompts and video content. This ensures robust preservation of original video elements while effectively applying the desired edits. Beyond its native video editing capability, we extend V$^2$Edit to 3D scene editing via a "render-edit-reconstruct" process, enabling high-quality, 3D-consistent edits even for tasks involving substantial geometric changes such as object insertion. Extensive experiments demonstrate that our V$^2$Edit achieves high-quality and successful edits across various challenging video editing tasks and complex 3D scene editing tasks, thereby establishing state-of-the-art performance in both domains.

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