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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 176–200 of 419 papers

TitleStatusHype
Interpretable 3D Human Action Analysis with Temporal Convolutional NetworksCode0
In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action RecognitionCode0
Part-based Graph Convolutional Network for Action RecognitionCode0
Actional-Structural Graph Convolutional Networks for Skeleton-based Action RecognitionCode0
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNNCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action RecognitionCode0
Cross-modal Learning by Hallucinating Missing Modalities in RGB-D VisionCode0
Improving Skeleton-based Action Recognition with Interactive Object InformationCode0
NTU RGB+D: A Large Scale Dataset for 3D Human Activity AnalysisCode0
Non-Local Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
On Geometric Features for Skeleton-Based Action Recognition using Multilayer LSTM NetworksCode0
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
A Comparative Review of Recent Kinect-based Action Recognition AlgorithmsCode0
Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action RecognitionCode0
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
Convolutional Neural Networks on Graphs with Fast Localized Spectral FilteringCode0
Human Action Recognition by Representing 3D Skeletons as Points in a Lie GroupCode0
Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognitionCode0
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action RecognitionCode0
High-Performance Inference Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
Attack-Augmentation Mixing-Contrastive Skeletal Representation LearningCode0
Hierarchical Temporal Convolution Network:Towards Privacy-Centric Activity RecognitionCode0
Action Recognition in Real-World Ambient Assisted Living EnvironmentCode0
Hierarchical growing grid networks for skeleton based action recognitionCode0
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