Shape-aware Text-driven Layered Video Editing

• URL: http://arxiv.org/abs/2301.13173v1
• Date: Mon, 30 Jan 2023 18:41:58 GMT
• Title: Shape-aware Text-driven Layered Video Editing
• Authors: Yao-Chih Lee, Ji-Ze Genevieve Jang, Yi-Ting Chen, Elizabeth Qiu, Jia-Bin Huang
• Abstract summary: We present a shape-aware, text-driven video editing method to handle shape changes. We first propagate the deformation field between the input and edited to all frames. We then leverage a pre-trained text-conditioned diffusion model as guidance for refining shape distortion and completing unseen regions.
• Score: 39.56765973770167
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Temporal consistency is essential for video editing applications. Existing work on layered representation of videos allows propagating edits consistently to each frame. These methods, however, can only edit object appearance rather than object shape changes due to the limitation of using a fixed UV mapping field for texture atlas. We present a shape-aware, text-driven video editing method to tackle this challenge. To handle shape changes in video editing, we first propagate the deformation field between the input and edited keyframe to all frames. We then leverage a pre-trained text-conditioned diffusion model as guidance for refining shape distortion and completing unseen regions. The experimental results demonstrate that our method can achieve shape-aware consistent video editing and compare favorably with the state-of-the-art.

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