DensityKV: Density-Guided KV Cache Compression for Long Video Generation
Autoregressive video diffusion models enable streaming generation through sliding-window attention, but each generated block is conditioned on previously generated content, causing appearance and motion errors to propagate recursively over time. Historical key-value (KV) memory preserves earlier subject and scene states and helps maintain long-horizon consistency. However, retaining every generated state creates a historical archive that grows continuously with the rollout, while recurrent states repeatedly add redundant coverage. To address this problem, we propose DensityKV, a training-free historical KV bank management strategy. DensityKV maintains a separate token-level KV bank for ea...
| Authors | Wenqu Zhao, Xuemin Chi, Xin Zhang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 28 August 2026 |
| Last updated at source | 28 August 2026 |
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