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Skeleton Based Action Recognition

Skeleton-based Action Recognition is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices. The goal of skeleton-based action recognition is to develop algorithms that can understand and classify human actions from skeleton data, which can be used in various applications such as human-computer interaction, sports analysis, and surveillance.

( Image credit: View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition )

Papers

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Showing 201–225 of 419 papers

TitleStatusHype
Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional ConnectivityCode1
Hierarchical Graph Convolutional Skeleton Transformer for Action Recognition—0
The Multi-Modal Video Reasoning and Analyzing Competition—0
Learning Skeletal Graph Neural Networks for Hard 3D Pose EstimationCode0
Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action RecognitionCode1
Skeleton-Contrastive 3D Action Representation LearningCode1
Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action RecognitionCode1
UNIK: A Unified Framework for Real-world Skeleton-based Action RecognitionCode1
Constructing Stronger and Faster Baselines for Skeleton-based Action RecognitionCode1
VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily LivingCode1
Fusing Higher-order Features in Graph Neural Networks for Skeleton-based Action RecognitionCode1
Revisiting Skeleton-based Action RecognitionCode1
Hierarchical growing grid networks for skeleton based action recognitionCode0
Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition—0
AdaSGN: Adapting Joint Number and Model Size for Efficient Skeleton-Based Action Recognition—0
Skeleton Aware Multi-modal Sign Language RecognitionCode1
Understanding the Robustness of Skeleton-based Action Recognition under Adversarial AttackCode1
Domain and View-point Agnostic Hand Action RecognitionCode0
Efficient Multi-stream Temporal Learning and Post-fusion Strategy for 3D Skeleton-based Hand Activity Recognition—0
NTU-X: An Enhanced Large-scale Dataset for Improving Pose-based Recognition of Subtle Human ActionsCode1
Geometric Deep Neural Network Using Rigid and Non-Rigid Transformations for Human Action Recognition—0
Self-Supervised 3D Skeleton Action Representation Learning With Motion Consistency and Continuity—0
Action Recognition with Kernel-based Graph Convolutional Networks—0
Tensor Representations for Action RecognitionCode1
Temporal Graph Modeling for Skeleton-based Action Recognition—0
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