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 101–110 of 1149 papers

TitleStatusHype
VideoMultiAgents: A Multi-Agent Framework for Video Question AnsweringCode1
TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming VideosCode3
TimeSoccer: An End-to-End Multimodal Large Language Model for Soccer Commentary Generation—0
DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs—0
IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMsCode1
Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language ModelsCode4
An LMM for Efficient Video Understanding via Reinforced Compression of Video Cubes—0
OmniV-Med: Scaling Medical Vision-Language Model for Universal Visual Understanding—0
ResNetVLLM -- Multi-modal Vision LLM for the Video Understanding Task—0
Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video UnderstandingCode0
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