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See4D: Pose-Free 4D Generation via Auto-Regressive Video Inpainting

Lu, Dongyue et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognitiongraphics
Immersive applications call for synthesizing spatiotemporal 4D content from casual videos without costly 3D supervision. Existing video-to-4D methods typically rely on manually annotated camera poses, which are labor-intensive and brittle for in-the-wild footage. Recent warp-then-inpaint approaches
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