SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–525 of 744 papers

TitleStatusHype
Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers—0
Human Activity Recognition using Deep Learning Models on Smartphones and Smartwatches Sensor Data—0
Transfer Learning for Future Wireless Networks: A Comprehensive Survey—0
SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled DataCode1
Improving state estimation through projection post-processing for activity recognition with application to footballCode0
AHAR: Adaptive CNN for Energy-efficient Human Activity Recognition in Low-power Edge Devices—0
Provably Secure Federated Learning against Malicious Clients—0
Cross-domain Activity Recognition via Substructural Optimal Transport—0
Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems—0
B-HAR: an open-source baseline framework for in depth study of human activity recognition datasets and workflowsCode0
Human Interaction Recognition Framework based on Interacting Body Part Attention—0
Machine-Generated Hierarchical Structure of Human Activities to Reveal How Machines Think—0
Human Activity Recognition Using Multichannel Convolutional Neural Network—0
A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity RecognitionCode0
Human Activity Recognition using Wearable Sensors: Review, Challenges, Evaluation BenchmarkCode1
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network—0
Dynamic Feature Selection for Efficient and Interpretable Human Activity Recognition—0
Deep Positive Unlabeled Learning with a Sequential Bias—0
SkipW: Resource adaptable RNN with strict upper computational limit—0
Invariant Feature Learning for Sensor-based Human Activity Recognition—0
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring—0
Contrastive Predictive Coding for Human Activity Recognition—0
Transfer Learning for Human Activity Recognition using Representational Analysis of Neural Networks—0
Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring—0
MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection—0
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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