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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 26–50 of 419 papers

TitleStatusHype
Language-Assisted Skeleton Action Understanding for Skeleton-Based Temporal Action SegmentationCode1
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition—0
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
Joint Mixing Data Augmentation for Skeleton-based Action RecognitionCode0
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
Spatial Hierarchy and Temporal Attention Guided Cross Masking for Self-supervised Skeleton-based Action RecognitionCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Zero-Shot Skeleton-based Action Recognition with Dual Visual-Text Alignment—0
SHARP: Segmentation of Hands and Arms by Range using Pseudo-Depth for Enhanced Egocentric 3D Hand Pose Estimation and Action RecognitionCode1
Joint Temporal Pooling for Improving Skeleton-based Action Recognition—0
Action Recognition for Privacy-Preserving Ambient Assisted LivingCode0
Signal-SGN: A Spiking Graph Convolutional Network for Skeletal Action Recognition via Learning Temporal-Frequency Dynamics—0
Skeleton-Based Action Recognition with Spatial-Structural Graph ConvolutionCode0
Joint-Partition Group Attention for skeleton-based action recognitionCode0
Multi-Modality Co-Learning for Efficient Skeleton-based Action RecognitionCode1
LORTSAR: Low-Rank Transformer for Skeleton-based Action Recognition—0
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational AutoencodersCode1
Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action RecognitionCode1
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed TransformerCode1
Do You Act Like You Talk? Exploring Pose-based Driver Action Classification with Speech Recognition NetworksCode0
STARS: Self-supervised Tuning for 3D Action Recognition in Skeleton SequencesCode1
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
Real-Time Hand Gesture Recognition: Integrating Skeleton-Based Data Fusion and Multi-Stream CNNCode1
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