Tetris decomposes stationary videos into tile polyominoes and applies classifier plus ILP pruning to cut detector calls, staying within 5% accuracy loss while delivering up to 17.4x throughput gains over priors.
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DragNUWA integrates text, image, and trajectory controls into a diffusion video model using a Trajectory Sampler, Multiscale Fusion, and Adaptive Training to enable fine-grained open-domain video generation.
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Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking
Tetris decomposes stationary videos into tile polyominoes and applies classifier plus ILP pruning to cut detector calls, staying within 5% accuracy loss while delivering up to 17.4x throughput gains over priors.
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DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory
DragNUWA integrates text, image, and trajectory controls into a diffusion video model using a Trajectory Sampler, Multiscale Fusion, and Adaptive Training to enable fine-grained open-domain video generation.