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 921–930 of 1149 papers

TitleStatusHype
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking—0
Technical Report: Temporal Aggregate RepresentationsCode1
Transformed ROIs for Capturing Visual Transformations in Videos—0
A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP—0
Highlight Timestamp Detection Model for Comedy Videos via Multimodal Sentiment Analysis—0
FineAction: A Fine-Grained Video Dataset for Temporal Action LocalizationCode1
VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding—0
NExT-QA:Next Phase of Question-Answering to Explaining Temporal ActionsCode1
MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports ActionsCode1
Relation-aware Hierarchical Attention Framework for Video Question AnsweringCode0
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