SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 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 RecognitionCode0
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 understandingCode0
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
Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition—0
Bootstrapped Representation Learning for Skeleton-Based Action Recognition—0
Towards To-a-T Spatio-Temporal Focus for Skeleton-Based Action Recognition—0
ADG-Pose: Automated Dataset Generation for Real-World Human Pose EstimationCode0
Real-World Graph Convolution Networks (RW-GCNs) for Action Recognition in Smart Video SurveillanceCode0
Spatio-Temporal Tuples Transformer for Skeleton-Based Action RecognitionCode1
InfoGCN: Representation Learning for Human Skeleton-Based Action RecognitionCode1
3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve—0
Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognition—0
Self-attention based anchor proposal for skeleton-based action recognition—0
Topology-aware Convolutional Neural Network for Efficient Skeleton-based Action RecognitionCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition—0
Anonymization for Skeleton Action RecognitionCode1
Contrast-reconstruction Representation Learning for Self-supervised Skeleton-based Action Recognition—0
Action Recognition with Domain Invariant Features of Skeleton Image—0
A Central Difference Graph Convolutional Operator for Skeleton-Based Action RecognitionCode0
Multi-Scale Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition—0
LSTA-Net: Long short-term Spatio-Temporal Aggregation Network for Skeleton-based Action RecognitionCode0
IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition—0
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognitionCode1
Sign Language Recognition via Skeleton-Aware Multi-Model EnsembleCode1
Unsupervised Motion Representation Learning with Capsule AutoencodersCode0
Fusion-GCN: Multimodal Action Recognition using Graph Convolutional NetworksCode1
Adversarial Bone Length Attack on Action Recognition—0
Show:102550
← PrevPage 4 of 9Next →

No leaderboard results yet.