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3D Action Recognition

Image: Rahmani et al

Papers

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Showing 1–50 of 91 papers

TitleStatusHype
A System for Real-Time Interactive Analysis of Deep Learning TrainingCode2
Grad-CAM++: Improved Visual Explanations for Deep Convolutional NetworksCode1
3DV: 3D Dynamic Voxel for Action Recognition in Depth VideoCode1
3DVNet: Multi-View Depth Prediction and Volumetric RefinementCode1
Unsupervised Learning of Object Keypoints for Perception and ControlCode1
TSM: Temporal Shift Module for Efficient Video UnderstandingCode1
STARS: Self-supervised Tuning for 3D Action Recognition in Skeleton SequencesCode1
Real-time 3D human action recognition based on Hyperpoint sequenceCode1
Revisiting Skeleton-based Action RecognitionCode1
Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural NetworksCode1
Reconstructing undersampled photoacoustic microscopy images using deep learningCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
PSTNet: Point Spatio-Temporal Convolution on Point Cloud SequencesCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud VideosCode1
On the Utility of 3D Hand Poses for Action RecognitionCode1
Deep Hierarchical Representation of Point Cloud Videos via Spatio-Temporal DecompositionCode1
No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time SurfacesCode1
Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action RecognitionCode1
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action RecognitionCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action RecognitionCode1
Masked Motion Predictors are Strong 3D Action Representation LearnersCode1
Leolani: a reference machine with a theory of mind for social communicationCode0
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural ActivitiesCode0
Fisherposes for Human Action Recognition Using Kinect Sensor DataCode0
Interpretable 3D Human Action Analysis with Temporal Convolutional NetworksCode0
Investigation of Different Skeleton Features for CNN-based 3D Action RecognitionCode0
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
NTU RGB+D: A Large Scale Dataset for 3D Human Activity AnalysisCode0
Recognizing Involuntary Actions from 3D Skeleton Data Using Body StatesCode0
Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action RecognitionCode0
SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action RecognitionCode0
Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference JointsCode0
Spatial Hierarchy and Temporal Attention Guided Cross Masking for Self-supervised Skeleton-based Action RecognitionCode0
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time WarpingCode0
3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning—0
Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons (Extended Version)—0
KAN-HyperpointNet for Point Cloud Sequence-Based 3D Human Action Recognition—0
Kernelized Covariance for Action Recognition—0
Learning clip representations for skeleton-based 3d action recognition—0
Learning Scene Flow With Skeleton Guidance For 3D Action Recognition—0
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks—0
3D Action Recognition From Novel Viewpoints—0
Localized Trajectories for 2D and 3D Action Recognition—0
DWnet: Deep-Wide Network for 3D Action Recognition—0
Mimetics: Towards Understanding Human Actions Out of Context—0
Mining Mid-level Features for Action Recognition Based on Effective Skeleton Representation—0
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All datasetsAssembly101NTU RGB+D100 sleep nights of 8 caregivers

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HandFormer-B/21Actions Top-141.06—Unverified
2TSMActions Top-135.27—Unverified
3RGBPoseConv3DActions Top-133.61—Unverified
4MS-G3DActions Top-128.7—Unverified
5ISTA-NetActions Top-128.07—Unverified
6CHASE(CTR-GCN)Actions Top-128.03—Unverified
72s-AGCNActions Top-126.7—Unverified
#ModelMetricClaimedVerifiedStatus
1KinetCross Subject Accuracy92.3—Unverified
2PSTNet++Cross Subject Accuracy91.4—Unverified
3PSTNetCross Subject Accuracy90.5—Unverified
4P4TransformerCross Subject Accuracy90.2—Unverified
53DV-PointNet++Cross Subject Accuracy88.8—Unverified
#ModelMetricClaimedVerifiedStatus
1htf10%4—Unverified