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 51–75 of 419 papers

TitleStatusHype
Navigating Open Set Scenarios for Skeleton-based Action RecognitionCode1
Neural Koopman Pooling: Control-Inspired Temporal Dynamics Encoding for Skeleton-Based Action RecognitionCode1
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action RecognitionCode1
Continual Spatio-Temporal Graph Convolutional NetworksCode1
Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action RecognitionCode1
Decoupling GCN with DropGraph Module for Skeleton-Based Action RecognitionCode1
A Dense-Sparse Complementary Network for Human Action Recognition based on RGB and Skeleton ModalitiesCode1
PREDICT & CLUSTER: Unsupervised Skeleton Based Action RecognitionCode1
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket SportsCode1
DSTSA-GCN: Advancing Skeleton-Based Gesture Recognition with Semantic-Aware Spatio-Temporal Topology ModelingCode1
Quo Vadis, Action Recognition? A New Model and the Kinetics DatasetCode1
Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the ArtCode1
GCN-DevLSTM: Path Development for Skeleton-Based Action RecognitionCode1
Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing AugmentationsCode1
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed TransformerCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
Constructing Stronger and Faster Baselines for Skeleton-based Action RecognitionCode1
Graph Attention NetworksCode1
Graph Contrastive Learning for Skeleton-based Action RecognitionCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Infrared and 3D skeleton feature fusion for RGB-D action recognitionCode1
Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action RecognitionCode1
MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D VideosCode1
Show:102550
← PrevPage 3 of 17Next →

No leaderboard results yet.