arXiv Computer Vision
3d ago

Memory Forcing: Attendable Mid-Horizon History for Streaming Video Generation

Memory Forcing is a new few‑step streaming method for autoregressive video diffusion that keeps a diverse mid‑horizon history without enlarging the KV cache. It partitions the cache into Archive, Working, and sink banks, and uses Bank‑aware RoPE to keep each bank distinguishable even as absolute temporal indices drift. Experiments show that at 1.3B parameters it outperforms other methods on longer clips, maintains subjects and scenes when they leave and re‑enter the window, and scales to a 5B model that produces more realistic, dynamic videos.

By Jiaming Zhang, Xinyu Wang, Huafeng Shi, Gangshan Wu, Limin Wang
arXiv Computer Vision
Sep 2

StreamScout: Learning When to Look Deeper for Streaming Video Understanding

arXiv:2609.00291v1 Announce Type: new Abstract: Streaming video understanding requires answering questions that arrive at arbitrary moments over an unbounded video stream. Existing systems primarily...

By Ce Zhang, Jing Bi, Jinxi He, Jianshu Zhang, Jingyang Lin, Yunzhong Xiao, Minghao Fu, Yaqi Xie, Zhentao Xie, Weicong Chen, Katia Sycara, Ming Zhou