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 751–760 of 1149 papers

TitleStatusHype
Gaze-Guided Graph Neural Network for Action Anticipation Conditioned on Intention—0
Koala: Key frame-conditioned long video-LLM—0
BioVL-QR: Egocentric Biochemical Vision-and-Language Dataset Using Micro QR Codes—0
OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning—0
R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding—0
R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding—0
Instrument-tissue Interaction Detection Framework for Surgical Video Understanding—0
A Unified Framework for Human-centric Point Cloud Video Understanding—0
Towards Multimodal Video Paragraph Captioning Models Robust to Missing ModalityCode0
Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding—0
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