Egocentric video provides a continuous first-person record of everyday activities, making it a natural foundation for wearable AI assistants. Unlike offline video understanding, streaming systems must process observations as they arrive, while queries may refer to experiences from the distant past. Recent work has begu...
Hao-Kai Pang, Yu-Qian Fu, Yi-Fei Wang et al.· 0 citations
Egocentric video understanding spans diverse capabilities, modalities, and evaluation formats, yet these are often studied in isolation despite their tight coupling in real-world interaction. We propose the Ego-Action-World interaction loop as a unifying principle: the wearer perceives the world, forms goals, acts, cha...
Song-Ruo Chen, Yu-Qian Fu, Yu Li et al.· 0 citations
This work proposes HyGAE, an actor-critic framework that jointly optimizes token- and turn-level objectives with the hybrid advantage and unified critic and provides an in-depth analysis showing that the exact analytic form of the hybrid advantage and return is crucial for optimization.
Streaming video understanding requires models to continuously retain useful visual evidence before future questions are known. Existing approaches primarily manage the growing visual context according to token importance, temporal redundancy, or segment-level relevance, but rarely organize evidence around objects that...
Mingkang Dong, Muxin Pu, Jie Li et al.· arXiv.org· 1 citation
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