SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 744 papers

TitleStatusHype
FLOW: Fusing and Shuffling Global and Local Views for Cross-User Human Activity Recognition with IMUs—0
iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets—0
Wearable-based behaviour interpolation for semi-supervised human activity recognition—0
Beyond Isolated Frames: Enhancing Sensor-Based Human Activity Recognition through Intra- and Inter-Frame Attention—0
NERULA: A Dual-Pathway Self-Supervised Learning Framework for Electrocardiogram Signal Analysis—0
A Masked Semi-Supervised Learning Approach for Otago Micro Labels Recognition—0
A Multi-Modal Explainability Approach for Human-Aware Robots in Multi-Party Conversation—0
Layout Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)—0
Millimeter Wave Radar-based Human Activity Recognition for Healthcare Monitoring Robot—0
SoK: Behind the Accuracy of Complex Human Activity Recognition Using Deep Learning—0
Unimodal and Multimodal Sensor Fusion for Wearable Activity Recognition—0
A Survey on Multimodal Wearable Sensor-based Human Action Recognition—0
Comparing Self-Supervised Learning Techniques for Wearable Human Activity RecognitionCode1
Transportation mode recognition based on low-rate acceleration and location signals with an attention-based multiple-instance learning network—0
Human Activity Recognition using Smartphones—0
MESEN: Exploit Multimodal Data to Design Unimodal Human Activity Recognition with Few Labels—0
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional MambaCode0
Multi-channel Time Series Decomposition Network For Generalizable Sensor-Based Activity Recognition—0
CODA: A COst-efficient Test-time Domain Adaptation Mechanism for HAR—0
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition—0
DiTMoS: Delving into Diverse Tiny-Model Selection on MicrocontrollersCode0
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer—0
Deep Generative Domain Adaptation with Temporal Attention for Cross-User Activity Recognition—0
Cross-user activity recognition using deep domain adaptation with temporal relation information—0
Machine Learning Techniques for Sensor-based Human Activity Recognition with Data Heterogeneity -- A Review—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