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Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 676–700 of 744 papers

TitleStatusHype
WiFlexFormer: Efficient WiFi-Based Person-Centric SensingCode0
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable SensorsCode0
Glimpse Clouds: Human Activity Recognition from Unstructured Feature PointsCode0
Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity RecognitionCode0
Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data ScarcityCode0
Learning Latent Sub-events in Activity Videos Using Temporal Attention FiltersCode0
ActiveHARNet: Towards On-Device Deep Bayesian Active Learning for Human Activity RecognitionCode0
Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial SensorsCode0
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptationCode0
Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous DataCode0
Hard Regularization to Prevent Deep Online Clustering Collapse without Data AugmentationCode0
Enhancing Wearable Tap Water Audio Detection through Subclass Annotation in the HD-Epic DatasetCode0
Enhanced Spatio- Temporal Image Encoding for Online Human Activity RecognitionCode0
Leveraging LDA Feature Extraction to Augment Human Activity Recognition AccuracyCode0
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional MambaCode0
A Training Framework for Optimal and Stable Training of Polynomial Neural NetworksCode0
Skeleton-Based Action Recognition with Spatial-Structural Graph ConvolutionCode0
DeepConvContext: A Multi-Scale Approach to Timeseries Classification in Human Activity RecognitionCode0
Attention-Refined Unrolling for Sparse Sequential micro-Doppler ReconstructionCode0
Efficient Deep Clustering of Human Activities and How to Improve EvaluationCode0
AdaRNN: Adaptive Learning and Forecasting of Time SeriesCode0
SALIENCE: An Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity RecognitionCode0
Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity RecognitionCode0
Unsupervised Deep Learning-based clustering for Human Activity RecognitionCode0
Weak-Annotation of HAR Datasets using Vision Foundation ModelsCode0
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All datasetsRHMOAD datasetPAMAP2HARHMDB51MM-FitRadar Dataset (DIAT-μRadHAR: Radar micro-Doppler Signature dataset for Human Suspicious Activity Recognition)UCF-101

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Dual-Stream C3DAccuracy (Top-1)71.06—Unverified
2C3DAccuracy (Top-1)70.3—Unverified
3Dual-Stream ConvNetAccuracy (Top-1)62.77—Unverified
4SlowFast (101)Accuracy (Top-1)45.28—Unverified
#ModelMetricClaimedVerifiedStatus
1ESTIE + VGG16 (transfer-learning)Accuracy95.22—Unverified
2STIE + VGG16 (transfer-learning)Accuracy94.77—Unverified
3STIE + VGG16(fine-tuning)Accuracy86.81—Unverified
#ModelMetricClaimedVerifiedStatus
1AFVFAccuracy0.97—Unverified
2Selective HAR ClusteringNMI0.88—Unverified
3Unsupervised embedding learning for human activity recognition using wearable sensor dataNMI0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1LMSSAccuracy1—Unverified
2AFVFAccuracy0.99—Unverified
#ModelMetricClaimedVerifiedStatus
1Label-RankerAccuracy61.18—Unverified
#ModelMetricClaimedVerifiedStatus
1unsupervised statistical feature guided diffusion modelF1 - macro0.44—Unverified
#ModelMetricClaimedVerifiedStatus
1DIAT-RadHARNet1:1 Accuracy99.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Label-RankerAccuracy89.5—Unverified