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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 276–300 of 419 papers

TitleStatusHype
Action Recognition with Kernel-based Graph Convolutional Networks—0
Recognizing Human Actions as the Evolution of Pose Estimation Maps—0
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition—0
Totally Deep Support Vector Machines—0
Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition—0
CrossGLG: LLM Guides One-shot Skeleton-based 3D Action Recognition in a Cross-level Manner—0
Towards a Skeleton-Based Action Recognition For Realistic Scenarios—0
Towards To-a-T Spatio-Temporal Focus for Skeleton-Based Action Recognition—0
Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data—0
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition—0
Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks—0
SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching—0
What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition—0
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition—0
Self-attention based anchor proposal for skeleton-based action recognition—0
Self-Attention Network for Skeleton-based Human Action Recognition—0
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization—0
Self-Supervised 3D Skeleton Action Representation Learning With Motion Consistency and Continuity—0
Contrast-reconstruction Representation Learning for Self-supervised Skeleton-based Action Recognition—0
Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition—0
View-Invariant Skeleton-based Action Recognition via Global-Local Contrastive Learning—0
Context Aware Graph Convolution for Skeleton-Based Action Recognition—0
Context-Aware Cross-Attention for Skeleton-Based Human Action Recognition—0
Unifying Graph Embedding Features with Graph Convolutional Networks for Skeleton-based Action Recognition—0
Action Recognition with Domain Invariant Features of Skeleton Image—0
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