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 821–830 of 1149 papers

TitleStatusHype
PYSKL: a toolbox for skeleton-based video understanding—0
SPAct: Self-supervised Privacy Preservation for Action RecognitionCode1
How Severe is Benchmark-Sensitivity in Video Self-Supervised Learning?Code1
FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding TasksCode0
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-TrainingCode3
On the Pitfalls of Batch Normalization for End-to-End Video Learning: A Study on Surgical Workflow AnalysisCode0
Human Gaze Guided Attention for Surgical Activity Recognition—0
Multi-Scale Self-Contrastive Learning with Hard Negative Mining for Weakly-Supervised Query-based Video Grounding—0
Temporal Perceiver: A General Architecture for Arbitrary Boundary Detection—0
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
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