64 citations · 64 across the 7 of their papers we have counts for
5 papers · 1 filter
Improving Video Sparse Attention with Fine-grained Router and Sparse Rebasing
Peiyuan Zhang, Guoqiang Wei, Yilong Zhao +7
We present VSA2, a frontier trainable sparse attention for video DiTs. VSA2 includes a variety of new architectural features and training procedures that we apply across all stages…
VSA: Faster Video Diffusion with Trainable Sparse Attention
Peiyuan Zhang, Yongqi Chen, Haofeng Huang +5
Scaling video diffusion transformers (DiTs) is limited by their quadratic 3D attention, even though most of the attention mass concentrates on a small subset of positions. We turn…
Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile
Hangliang Ding, Dacheng Li, Runlong Su +4
Despite the promise of synthesizing high-fidelity videos, Diffusion Transformers (DiTs) with 3D full attention suffer from expensive inference due to the complexity of attention co…
Fast Video Generation with Sliding Tile Attention
Peiyuan Zhang, Yongqi Chen, Runlong Su +4
Diffusion Transformers (DiTs) with 3D full attention power state-of-the-art video generation, but suffer from prohibitive compute cost -- when generating just a 5-second 720P video…
Temporal Reasoning Transfer from Text to Video
Lei Li, Yuanxin Liu, Linli Yao +6
Video Large Language Models (Video LLMs) have shown promising capabilities in video comprehension, yet they struggle with tracking temporal changes and reasoning about temporal rel…