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 831–840 of 1149 papers

TitleStatusHype
From Trial to Triumph: Advancing Long Video Understanding via Visual Context Sample Scaling and Self-reward Alignment—0
Fully Automated Hand Hygiene Monitoring\ Operating Room using 3D Convolutional Neural Network—0
Future semantic segmentation of time-lapsed videos with large temporal displacement—0
Gameplay Highlights Generation—0
Gaze-Guided Graph Neural Network for Action Anticipation Conditioned on Intention—0
Generating the Future With Adversarial Transformers—0
Generating Videos with Scene Dynamics—0
Generative Frame Sampler for Long Video Understanding—0
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning—0
GEXIA: Granularity Expansion and Iterative Approximation for Scalable Multi-grained Video-language Learning—0
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