5 papers · 1 filter
Agentic Very Long Video Understanding
Aniket Rege, Arka Sadhu, Yuliang Li +5
The advent of always-on personal AI assistants, enabled by all-day wearable devices such as smart glasses, demands a new level of contextual understanding, one that goes beyond sho…
Reading Recognition in the Wild
Charig Yang, Samiul Alam, Shakhrul Iman Siam +12
To enable egocentric contextual AI in always-on smart glasses, it is crucial to be able to keep a record of the user's interactions with the world, including during reading. In thi…
CountSteer: Steering Attention for Object Counting in Diffusion Models
Hyemin Boo, Hyoryung Kim, Myungjin Lee +4
Text-to-image diffusion models generate realistic and coherent images but often fail to follow numerical instructions in text, revealing a gap between language and visual represent…
EgoLM: Multi-Modal Language Model of Egocentric Motions
Fangzhou Hong, Vladimir Guzov, Hyo Jin Kim +4
As the prevalence of wearable devices, learning egocentric motions becomes essential to develop contextual AI. In this work, we present EgoLM, a versatile framework that tracks and…
Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild
Lingni Ma, Yuting Ye, Fangzhou Hong +14
We introduce Nymeria - a large-scale, diverse, richly annotated human motion dataset collected in the wild with multiple multimodal egocentric devices. The dataset comes with a) fu…