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.