Sparse Attention for Video Generation

CalibAtt, a training-free method, accelerates text-to-video generation by identifying and skipping negligible token-to-token connections in transformer-based diffusion models. It achieves up to 1.58x end-to-end speedup while maintaining video generation quality and text-video alignment by performing an offline calibration pass to compile block-level sparsity and repetition patterns into optimized attention operations.