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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 101–150 of 419 papers

TitleStatusHype
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation—0
Action Recognition with Multi-stream Motion Modeling and Mutual Information MaximizationCode0
How Object Information Improves Skeleton-based Human Action Recognition in Assembly Tasks—0
High-Performance Inference Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
Fourier Analysis on Robustness of Graph Convolutional Neural Networks for Skeleton-based Action RecognitionCode0
Language Knowledge-Assisted Representation Learning for Skeleton-Based Action RecognitionCode1
Overcoming Topology Agnosticism: Enhancing Skeleton-Based Action Recognition through Redefined Skeletal Topology AwarenessCode1
Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognitionCode0
Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition—0
Temporal Decoupling Graph Convolutional Network for Skeleton-based Gesture RecognitionCode1
Part Aware Contrastive Learning for Self-Supervised Action RecognitionCode1
TSGCNeXt: Dynamic-Static Multi-Graph Convolution for Efficient Skeleton-Based Action Recognition with Long-term Learning PotentialCode1
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization—0
Skeleton-based action analysis for ADHD diagnosis—0
Attack-Augmentation Mixing-Contrastive Skeletal Representation LearningCode0
Focalized Contrastive View-invariant Learning for Self-supervised Skeleton-based Action Recognition—0
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of ActionsCode0
Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling—0
3Mformer: Multi-order Multi-mode Transformer for Skeletal Action Recognition—0
Actionlet-Dependent Contrastive Learning for Unsupervised Skeleton-Based Action Recognition—0
HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action RepresentationsCode1
Learning Discriminative Representations for Skeleton Based Action RecognitionCode1
Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition—0
Temporal-Channel Topology Enhanced Network for Skeleton-Based Action RecognitionCode0
DMMG: Dual Min-Max Games for Self-Supervised Skeleton-Based Action Recognition—0
Dynamic Spatial-temporal Hypergraph Convolutional Network for Skeleton-based Action Recognition—0
Self-supervised Action Representation Learning from Partial Spatio-Temporal Skeleton SequencesCode1
Spatiotemporal Decouple-and-Squeeze Contrastive Learning for Semi-Supervised Skeleton-based Action Recognition—0
Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action RecognitionCode0
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
Graph Contrastive Learning for Skeleton-based Action RecognitionCode1
Parallel Attention Interaction Network for Few-Shot Skeleton-Based Action Recognition—0
Modeling the Relative Visual Tempo for Self-supervised Skeleton-based Action RecognitionCode0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild—0
Neural Koopman Pooling: Control-Inspired Temporal Dynamics Encoding for Skeleton-Based Action RecognitionCode1
Leveraging Spatio-Temporal Dependency for Skeleton-Based Action RecognitionCode1
Hierarchical Contrast for Unsupervised Skeleton-based Action Representation LearningCode1
Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing AugmentationsCode1
Hypergraph Transformer for Skeleton-based Action RecognitionCode1
Temporal-Viewpoint Transportation Plan for Skeletal Few-shot Action Recognition—0
MotionBERT: A Unified Perspective on Learning Human Motion RepresentationsCode3
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
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