SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–500 of 744 papers

TitleStatusHype
HAR-DoReMi: Optimizing Data Mixture for Self-Supervised Human Activity Recognition Across Heterogeneous IMU Datasets—0
HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?—0
HAR-Net:Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition—0
Heterogeneous Hyper-Graph Neural Networks for Context-aware Human Activity Recognition—0
Heterogeneous Relationships of Subjects and Shapelets for Semi-supervised Multivariate Series Classification—0
Homogenization of Existing Inertial-Based Datasets to Support Human Activity Recognition—0
Human Action Attribute Learning From Video Data Using Low-Rank Representations—0
Human Activity Analysis and Recognition from Smartphones using Machine Learning Techniques—0
Human Activity Behavioural Pattern Recognition in Smarthome with Long-hour Data Collection—0
Human Activity Prediction in Smart Home Environments with LSTM Neural Networks—0
Human Activity Recognition based on Dynamic Spatio-Temporal Relations—0
Human activity recognition based on time series analysis using U-Net—0
Human Activity Recognition for Edge Devices—0
Human Activity Recognition for Mobile Robot—0
Human activity recognition from mobile inertial sensors using recurrence plots—0
Human Activity Recognition from Wi-Fi CSI Data Using Principal Component-Based Wavelet CNN—0
Human Activity Recognition in RGB-D Videos by Dynamic Images—0
Human Activity Recognition Models in Ontology Networks—0
Human Activity Recognition models using Limited Consumer Device Sensors and Machine Learning—0
Human Activity Recognition on Microcontrollers with Quantized and Adaptive Deep Neural Networks—0
Human Activity Recognition on Time Series Accelerometer Sensor Data using LSTM Recurrent Neural Networks—0
Human Activity Recognition on wrist-worn accelerometers using self-supervised neural networks—0
Human Activity Recognition Using 3D Orthogonally-projected EfficientNet on Radar Time-Range-Doppler Signature—0
Human Activity Recognition using Attribute-Based Neural Networks and Context Information—0
Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework—0
Human Activity Recognition using Deep Learning Models on Smartphones and Smartwatches Sensor Data—0
Human activity recognition using deep learning approaches and single frame cnn and convolutional lstm—0
Human activity recognition using improved dynamic image—0
Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey—0
Human Activity Recognition Using LSTM-RNN Deep Neural Network Architecture—0
Human Activity Recognition Using Multichannel Convolutional Neural Network—0
Human Activity Recognition using Recurrent Neural Networks—0
Human Activity Recognition Using Robust Adaptive Privileged Probabilistic Learning—0
Human Activity Recognition Using Self-Supervised Representations of Wearable Data—0
Human Activity Recognition using Smartphone—0
Human Activity Recognition using Smartphones—0
Human Activity Recognition Using Tools of Convolutional Neural Networks: A State of the Art Review, Data Sets, Challenges and Future Prospects—0
Human Activity Recognition with a 6.5 GHz Reconfigurable Intelligent Surface for Wi-Fi 6E—0
Human Activity Recognition with Low-Resolution Infrared Array Sensor Using Semi-supervised Cross-domain Neural Networks for Indoor Environment—0
Human Body Parts Tracking: Applications to Activity Recognition—0
Human Interaction Recognition Framework based on Interacting Body Part Attention—0
Human Pose Estimation using Motion Priors and Ensemble Models—0
Hybrid Model Featuring CNN and LSTM Architecture for Human Activity Recognition on Smartphone Sensor Data—0
iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets—0
iMove: Exploring Bio-impedance Sensing for Fitness Activity Recognition—0
Impact of Physical Activity on Sleep:A Deep Learning Based Exploration—0
Importance of user inputs while using incremental learning to personalize human activity recognition models—0
Improve Unsupervised Domain Adaptation with Mixup Training—0
Improving Human Activity Recognition Through Ranking and Re-ranking—0
IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition—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