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 551–560 of 1149 papers

TitleStatusHype
A Unified Framework for Human-centric Point Cloud Video Understanding—0
Towards Multimodal Video Paragraph Captioning Models Robust to Missing ModalityCode0
OmniVid: A Generative Framework for Universal Video UnderstandingCode2
Understanding Long Videos with Multimodal Language ModelsCode2
Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding—0
InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingCode7
VURF: A General-purpose Reasoning and Self-refinement Framework for Video UnderstandingCode0
Language Repository for Long Video UnderstandingCode1
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object SegmentationCode1
VideoAgent: A Memory-augmented Multimodal Agent for Video Understanding—0
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