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 651–660 of 1149 papers

TitleStatusHype
ViFi-ReID: A Two-Stream Vision-WiFi Multimodal Approach for Person Re-identification—0
Prompting Video-Language Foundation Models with Domain-specific Fine-grained Heuristics for Video Question Answering—0
TVBench: Redesigning Video-Language Evaluation—0
MM-Ego: Towards Building Egocentric Multimodal LLMs—0
Enhancing Multimodal LLM for Detailed and Accurate Video Captioning using Multi-Round Preference Optimization—0
Enhancing Temporal Modeling of Video LLMs via Time GatingCode0
AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark—0
Frame-Voyager: Learning to Query Frames for Video Large Language Models—0
DTVLT: A Multi-modal Diverse Text Benchmark for Visual Language Tracking Based on LLM—0
AirLetters: An Open Video Dataset of Characters Drawn in the Air—0
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