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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 151–200 of 419 papers

TitleStatusHype
Boosting Adversarial Transferability for Skeleton-based Action Recognition via Exploring the Model Posterior Space—0
Mask and Compress: Efficient Skeleton-based Action Recognition in Continual LearningCode0
Expressive Keypoints for Skeleton-based Action Recognition via Skeleton TransformationCode0
An Information Compensation Framework for Zero-Shot Skeleton-based Action Recognition—0
Skeleton-OOD: An End-to-End Skeleton-Based Model for Robust Out-of-Distribution Human Action DetectionCode0
Enhancing Action Recognition from Low-Quality Skeleton Data via Part-Level Knowledge Distillation—0
An Improved Graph Pooling Network for Skeleton-Based Action Recognition—0
MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition—0
In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action RecognitionCode0
Multi-Scale Spatial-Temporal Self-Attention Graph Convolutional Networks for Skeleton-based Action Recognition—0
LLMs are Good Action Recognizers—0
Skeleton-Based Human Action Recognition with Noisy LabelsCode0
CrossGLG: LLM Guides One-shot Skeleton-based 3D Action Recognition in a Cross-level Manner—0
Wavelet-Decoupling Contrastive Enhancement Network for Fine-Grained Skeleton-Based Action Recognition—0
AutoGCN -- Towards Generic Human Activity Recognition with Neural Architecture SearchCode0
Benchmarking Sensitivity of Continual Graph Learning for Skeleton-Based Action Recognition—0
Unsupervised Spatial-Temporal Feature Enrichment and Fidelity Preservation Network for Skeleton based Action Recognition—0
Skeleton2vec: A Self-supervised Learning Framework with Contextualized Target Representations for Skeleton SequenceCode0
MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning—0
Spatial-Temporal Decoupling Contrastive Learning for Skeleton-based Human Action RecognitionCode0
STEP CATFormer: Spatial-Temporal Effective Body-Part Cross Attention Transformer for Skeleton-based Action RecognitionCode0
SkelVIT: Consensus of Vision Transformers for a Lightweight Skeleton-Based Action Recognition System—0
Proving the Potential of Skeleton Based Action Recognition to Automate the Analysis of Manual Processes—0
Elevating Skeleton-Based Action Recognition with Efficient Multi-Modality Self-SupervisionCode0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild—0
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition—0
Balanced Representation Learning for Long-tailed Skeleton-based Action RecognitionCode0
Local Spherical Harmonics Improve Skeleton-Based Hand Action RecognitionCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Miniaturized Graph Convolutional Networks with Topologically Consistent Pruning—0
Multi-Dimensional Refinement Graph Convolutional Network with Robust Decouple Loss for Fine-Grained Skeleton-Based Action Recognition—0
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
Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognitionCode0
Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition—0
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
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
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