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Memory consistency in video generation models falters significantly when objects disappear, with state-of-the-art models struggling to recover updated states upon reappearance.
Deformable 3D reconstruction can be more than just visually plausible geometry; SEMAGIC shows it can also learn stable semantic correspondences, boosting performance by +14.7 PCK@0.1 on SPair-71k.
