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Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–475 of 744 papers

TitleStatusHype
Self-Supervised Learning for WiFi CSI-Based Human Activity Recognition: A Systematic Study—0
Self-supervised Human Activity Recognition by Learning to Predict Cross-Dimensional Motion—0
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition—0
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition—0
Semi-supervised Federated Learning for Activity Recognition—0
Semi-supervised sequence classification through change point detection—0
Sensing with OFDM Waveform at mmWave Band based on Micro-Doppler Analysis—0
Sensor-Based Data Acquisition via Ubiquitous Device to Detect Muscle Strength Training Activities—0
Sensor Data Augmentation by Resampling for Contrastive Learning in Human Activity Recognition—0
Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking—0
SETransformer: A Hybrid Attention-Based Architecture for Robust Human Activity Recognition—0
SHADE-AD: An LLM-Based Framework for Synthesizing Activity Data of Alzheimer's Patients—0
Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks—0
Shuffled Differentially Private Federated Learning for Time Series Data Analytics—0
Siamese Networks for Weakly Supervised Human Activity Recognition—0
Sign Language Recognition Analysis using Multimodal Data—0
SignX: The Foundation Model for Sign Recognition—0
Similarity Embedding Networks for Robust Human Activity Recognition—0
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition—0
Simultaneous Implementation Features Extraction and Recognition Using C3D Network for WiFi-based Human Activity Recognition—0
Simultaneous Joint and Object Trajectory Templates for Human Activity Recognition from 3-D Data—0
Simultaneous Learning from Human Pose and Object Cues for Real-Time Activity Recognition—0
Skeleton-based Activity Recognition with Local Order Preserving Match of Linear Patches—0
Skeleton Focused Human Activity Recognition in RGB Video—0
SkipW: Resource adaptable RNN with strict upper computational limit—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