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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 151–175 of 419 papers

TitleStatusHype
ViA: View-invariant Skeleton Action Representation Learning via Motion RetargetingCode1
Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action RecognitionCode1
Part-aware Prototypical Graph Network for One-shot Skeleton-based Action Recognition—0
Spatial Temporal Graph Attention Network for Skeleton-Based Action RecognitionCode1
PSUMNet: Unified Modality Part Streams are All You Need for Efficient Pose-based Action RecognitionCode1
Generative Action Description Prompts for Skeleton-based Action RecognitionCode1
AFE-CNN: 3D Skeleton-based Action Recognition with Action Feature Enhancement—0
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Learning from Temporal Spatial Cubism for Cross-Dataset Skeleton-based Action RecognitionCode0
Skeletal Human Action Recognition using Hybrid Attention based Graph Convolutional NetworkCode0
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Skeleton-based Action Recognition via Adaptive Cross-Form LearningCode0
A New Adjacency Matrix Configuration in GCN-based Models for Skeleton-based Action Recognition—0
Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action RecognitionCode1
Skeleton-based Action Recognition via Temporal-Channel AggregationCode1
MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D VideosCode1
PYSKL: Towards Good Practices for Skeleton Action Recognition—0
ANUBIS: Skeleton Action Recognition Dataset, Review, and Benchmark—0
A Spatio-Temporal Multilayer Perceptron for Gesture RecognitionCode1
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
Continual Spatio-Temporal Graph Convolutional NetworksCode1
Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse OcclusionsCode1
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