Preprint
Aug 2026
SCOPE: Subspace Clustering with Online Per-Head Top-K Estimation for Sparse Video Attention
SCOPE is a training-free sparse attention framework that combines 3D-RoPE-aligned key subspace clustering with online per-head Top-$k$ estimation for efficient video-DiT inference and consistently outperforms existing training-free baselines in both fidelity and latency.
Qi Zhao, Qi-Rui Li, Hanlin Tang et al.
· 0 citations