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 211–220 of 1149 papers

TitleStatusHype
Contrastive Spatio-Temporal Pretext Learning for Self-supervised Video RepresentationCode1
Contrastive Masked Autoencoders for Self-Supervised Video HashingCode1
MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports ActionsCode1
From Seconds to Hours: Reviewing MultiModal Large Language Models on Comprehensive Long Video UnderstandingCode1
AlanaVLM: A Multimodal Embodied AI Foundation Model for Egocentric Video UnderstandingCode1
From Representation to Reasoning: Towards both Evidence and Commonsense Reasoning for Video Question-AnsweringCode1
AVS-Mamba: Exploring Temporal and Multi-modal Mamba for Audio-Visual SegmentationCode1
Disentangle Your Dense Object DetectorCode1
From My View to Yours: Ego-Augmented Learning in Large Vision Language Models for Understanding Exocentric Daily Living ActivitiesCode1
Mug-STAN: Adapting Image-Language Pretrained Models for General Video UnderstandingCode1
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