SOTAVerified

Video Understanding

A crucial task of Video Understanding is to recognise and localise (in space and time) different actions or events appearing in the video.

Source: Action Detection from a Robot-Car Perspective

Papers

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Showing 771–780 of 1149 papers

TitleStatusHype
Dynamic Multistep Reasoning based on Video Scene Graph for Video Question Answering—0
DynFocus: Dynamic Cooperative Network Empowers LLMs with Video Understanding—0
DynTok: Dynamic Compression of Visual Tokens for Efficient and Effective Video Understanding—0
EAGLE: Egocentric AGgregated Language-video Engine—0
Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey—0
Efficient Modelling Across Time of Human Actions and Interactions—0
Efficient Motion-Aware Video MLLM—0
Efficient Video Understanding via Layered Multi Frame-Rate Analysis—0
EgoEnv: Human-centric environment representations from egocentric video—0
Egocentric Video Task Translation—0
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