AI RESEARCH
EgoReasoner: Learning Egocentric 4D Reasoning via Task-Adaptive Structured Thinking
arXiv CS.CV
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ArXi:2603.06561v1 Announce Type: new Egocentric video understanding is inherently complex due to the dynamic 4D nature of the environment, where camera motion and object displacements necessitate a continuous re-evaluation of spatial relations. In this work, we target a suite of under-explored egocentric 4D reasoning tasks, including fixture interaction counting, viewpoint-relative fixture location, object movement itinerary tracking, and stationary object localization, that require fundamentally different cognitive operations: spatial anchoring, temporal tracking, and duration reasoning.