StreamChat

Paper: Streaming Video Understanding and Multi-round Interaction with Memory-enhanced Knowledge Code: hmxiong/StreamChat Background Most Video-LLMs are still awkward in a real streaming setting. Offline video QA usually assumes: the whole video is already available; the question is known before inference; the interaction is single-turn. But a streaming assistant has a different problem: video frames keep arriving; the user may ask questions at arbitrary timestamps; the system should remember previous conversation turns; the answer should come back with low latency. This is close to the motivation of ReKV, Flash-VStream, LiveVLM, and rLiVS, but StreamChat chooses a different abstraction. ...