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 911–920 of 1149 papers

TitleStatusHype
Large-Scale YouTube-8M Video Understanding with Deep Neural Networks—0
LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision—0
Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detection—0
Learning Audio-guided Video Representation with Gated Attention for Video-Text Retrieval—0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking—0
Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment—0
Learning from Multiple Sources for Video Summarisation—0
Learning Higher-order Object Interactions for Keypoint-based Video Understanding—0
Learning Object State Changes in Videos: An Open-World Perspective—0
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