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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 251–260 of 1149 papers

TitleStatusHype
HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition—0
AVS-Mamba: Exploring Temporal and Multi-modal Mamba for Audio-Visual SegmentationCode1
Facial Dynamics in Video: Instruction Tuning for Improved Facial Expression Perception and Contextual AwarenessCode1
Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks—0
Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video UnderstandingCode4
MECD+: Unlocking Event-Level Causal Graph Discovery for Video ReasoningCode1
Video Quality Assessment for Online Processing: From Spatial to Temporal Sampling—0
VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video CaptioningCode1
X-LeBench: A Benchmark for Extremely Long Egocentric Video Understanding—0
From My View to Yours: Ego-Augmented Learning in Large Vision Language Models for Understanding Exocentric Daily Living ActivitiesCode1
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