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Videoshop: Localized Semantic Video Editing with Noise-Extrapolated Diffusion Inversion

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arxiv 2403.14617 v3 pith:E2KL7N3U submitted 2024-03-21 cs.CV cs.AIcs.LG

classification cs.CVcs.AIcs.LG
keywords editingvideoshopeditssemanticvideoallowslocalizedobjects
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We introduce Videoshop, a training-free video editing algorithm for localized semantic edits. Videoshop allows users to use any editing software, including Photoshop and generative inpainting, to modify the first frame; it automatically propagates those changes, with semantic, spatial, and temporally consistent motion, to the remaining frames. Unlike existing methods that enable edits only through imprecise textual instructions, Videoshop allows users to add or remove objects, semantically change objects, insert stock photos into videos, etc. with fine-grained control over locations and appearance. We achieve this through image-based video editing by inverting latents with noise extrapolation, from which we generate videos conditioned on the edited image. Videoshop produces higher quality edits against 6 baselines on 2 editing benchmarks using 10 evaluation metrics.

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Cited by 1 Pith paper

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  1. Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning

    cs.CV 2024-12 conditional novelty 6.0 of 10

    UES adds a self-supervised video condition to text-to-video diffusion models, enabling them to edit videos from delta prompts without paired supervision.

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