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 541–550 of 1149 papers

TitleStatusHype
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
LongVLM: Efficient Long Video Understanding via Large Language ModelsCode2
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual TokensCode4
SnAG: Scalable and Accurate Video GroundingCode4
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
ST-LLM: Large Language Models Are Effective Temporal LearnersCode2
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