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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 201–250 of 419 papers

TitleStatusHype
Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action RecognitionCode0
Spatiotemporal Decouple-and-Squeeze Contrastive Learning for Semi-Supervised Skeleton-based Action Recognition—0
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN)—0
Action Capsules: Human Skeleton Action Recognition—0
Skeleton-based Action Recognition through Contrasting Two-Stream Spatial-Temporal Networks—0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild—0
Parallel Attention Interaction Network for Few-Shot Skeleton-Based Action Recognition—0
Modeling the Relative Visual Tempo for Self-supervised Skeleton-based Action RecognitionCode0
Temporal-Viewpoint Transportation Plan for Skeletal Few-shot Action Recognition—0
DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action RecognitionCode0
Pose-Guided Graph Convolutional Networks for Skeleton-Based Action Recognition—0
Focal and Global Spatial-Temporal Transformer for Skeleton-based Action Recognition—0
View-Invariant Skeleton-based Action Recognition via Global-Local Contrastive Learning—0
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition—0
Shifting Perspective to See Difference: A Novel Multi-View Method for Skeleton based Action RecognitionCode0
SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition—0
Part-aware Prototypical Graph Network for One-shot Skeleton-based Action Recognition—0
AFE-CNN: 3D Skeleton-based Action Recognition with Action Feature Enhancement—0
Learning from Temporal Spatial Cubism for Cross-Dataset Skeleton-based Action RecognitionCode0
Skeletal Human Action Recognition using Hybrid Attention based Graph Convolutional NetworkCode0
Skeleton-based Action Recognition via Adaptive Cross-Form LearningCode0
A New Adjacency Matrix Configuration in GCN-based Models for Skeleton-based Action Recognition—0
PYSKL: Towards Good Practices for Skeleton Action Recognition—0
ANUBIS: Skeleton Action Recognition Dataset, Review, and Benchmark—0
Unsupervised Human Action Recognition with Skeletal Graph Laplacian and Self-Supervised Viewpoints InvarianceCode0
FenceNet: Fine-grained Footwork Recognition in Fencing—0
PYSKL: a toolbox for skeleton-based video understanding—0
SpatioTemporal Focus for Skeleton-based Action Recognition—0
Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition—0
Bootstrapped Representation Learning for Skeleton-Based Action Recognition—0
Towards To-a-T Spatio-Temporal Focus for Skeleton-Based Action Recognition—0
ADG-Pose: Automated Dataset Generation for Real-World Human Pose EstimationCode0
Real-World Graph Convolution Networks (RW-GCNs) for Action Recognition in Smart Video SurveillanceCode0
3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve—0
Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognition—0
Self-attention based anchor proposal for skeleton-based action recognition—0
Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition—0
Contrast-reconstruction Representation Learning for Self-supervised Skeleton-based Action Recognition—0
Action Recognition with Domain Invariant Features of Skeleton Image—0
A Central Difference Graph Convolutional Operator for Skeleton-Based Action RecognitionCode0
Multi-Scale Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition—0
LSTA-Net: Long short-term Spatio-Temporal Aggregation Network for Skeleton-based Action RecognitionCode0
IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition—0
Unsupervised Motion Representation Learning with Capsule AutoencodersCode0
Adversarial Bone Length Attack on Action Recognition—0
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
Hierarchical growing grid networks for skeleton based action recognitionCode0
Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition—0
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