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 981–990 of 1149 papers

TitleStatusHype
FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation FrameworkCode0
M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformers—0
Augmented Transformer with Adaptive Graph for Temporal Action Proposal Generation—0
Unified Graph Structured Models for Video Understanding—0
Low-Fidelity End-to-End Video Encoder Pre-training for Temporal Action Localization—0
ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation—0
Enhancing Transformer for Video Understanding Using Gated Multi-Level Attention and Temporal Adversarial Training—0
PcmNet: Position-Sensitive Context Modeling Network for Temporal Action Localization—0
Unsupervised Motion Representation Enhanced Network for Action Recognition—0
Win-Fail Action RecognitionCode0
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