AI Research
CapMem: A Benchmark for Caption-Based Episodic Memory in Egocentric Video
Bridging the gap between long-term episodic memory and efficient vision-language processing.
Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token costs, and long-context retrieval failures. Under these practical constraints, we study whether textual captions can serve as reu...
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ArXiv CS.AI
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ArXiv CS.AI
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CapMem shifts the focus from costly visual token processing to efficient text-based episodic retrieval for wearable AI systems. This approach addresses critical hardware constraints while providing a scalable framework for long-term memory in egocentric video applications.
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