SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 376–400 of 744 papers

TitleStatusHype
BSDGAN: Balancing Sensor Data Generative Adversarial Networks for Human Activity Recognition—0
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer—0
Domain Generalization for Activity Recognition via Adaptive Feature Fusion—0
Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition—0
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications—0
Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domain—0
Federated Continual Learning through distillation in pervasive computing—0
Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR—0
CHARM: A Hierarchical Deep Learning Model for Classification of Complex Human Activities Using Motion Sensors—0
SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human SensingCode2
Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity RecognitionCode0
WiFi-based Spatiotemporal Human Action Perception—0
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency ConsistencyCode2
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition—0
Beyond the Gates of Euclidean Space: Temporal-Discrimination-Fusions and Attention-based Graph Neural Network for Human Activity Recognition—0
Two-stage Human Activity Recognition on Microcontrollers with Decision Trees and CNNs—0
Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable DataCode1
Human Activity Recognition on Time Series Accelerometer Sensor Data using LSTM Recurrent Neural Networks—0
Ultra-compact Binary Neural Networks for Human Activity Recognition on RISC-V ProcessorsCode0
UMSNet: An Universal Multi-sensor Network for Human Activity Recognition—0
A Wireless-Vision Dataset for Privacy Preserving Human Activity Recognition—0
Contrastive Learning with Cross-Modal Knowledge Mining for Multimodal Human Activity RecognitionCode1
Classifying Human Activities using Machine Learning and Deep Learning Techniques—0
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes—0
SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems—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