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VideoSwap: Customized Video Subject Swapping with Interactive Semantic Point Correspondence

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arxiv 2312.02087 v2 pith:HH7UKNMW submitted 2023-12-04 cs.CV

VideoSwap: Customized Video Subject Swapping with Interactive Semantic Point Correspondence

classification cs.CV
keywords subjectvideosemanticshapecorrespondenceseditingpointpoints
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Current diffusion-based video editing primarily focuses on structure-preserved editing by utilizing various dense correspondences to ensure temporal consistency and motion alignment. However, these approaches are often ineffective when the target edit involves a shape change. To embark on video editing with shape change, we explore customized video subject swapping in this work, where we aim to replace the main subject in a source video with a target subject having a distinct identity and potentially different shape. In contrast to previous methods that rely on dense correspondences, we introduce the VideoSwap framework that exploits semantic point correspondences, inspired by our observation that only a small number of semantic points are necessary to align the subject's motion trajectory and modify its shape. We also introduce various user-point interactions (\eg, removing points and dragging points) to address various semantic point correspondence. Extensive experiments demonstrate state-of-the-art video subject swapping results across a variety of real-world videos.

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Cited by 1 Pith paper

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    cs.CV 2026-04 conditional novelty 6.0

    TRACE anchors a video-diffusion editor to 3D meshes to perform consistent part-level edits on 3D Gaussian scenes in about 10 minutes per edit.