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 931–940 of 1149 papers

TitleStatusHype
LiveVLM: Efficient Online Video Understanding via Streaming-Oriented KV Cache and Retrieval—0
LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering—0
LLaVA-MLB: Mitigating and Leveraging Attention Bias for Training-Free Video LLMs—0
LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding—0
LLAVIDAL: A Large LAnguage VIsion Model for Daily Activities of Living—0
LLM4Brain: Training a Large Language Model for Brain Video Understanding—0
LLMs Meet Long Video: Advancing Long Video Question Answering with An Interactive Visual Adapter in LLMs—0
Localizing Events in Videos with Multimodal Queries—0
Localizing Unseen Activities in Video via Image Query—0
Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understanding—0
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