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Re-encoding a compact set of distilled synthetic images during test-time adaptation dynamically realigns source anchors with shifting model weights, eliminating both catastrophic forgetting and pseudo-label drift under severe distribution shifts.
Clustering performance improves dramatically with DAS-PMVC, which effectively tackles the partial view alignment problem that plagues traditional multi-view methods.
Achieving precise control over human motion and camera trajectories in 3D scene animation could redefine the realism and interactivity of video generation.
