SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–325 of 744 papers

TitleStatusHype
Human activity recognition using deep learning approaches and single frame cnn and convolutional lstm—0
Contactless Human Activity Recognition using Deep Learning with Flexible and Scalable Software Define Radio—0
Explaining, Analyzing, and Probing Representations of Self-Supervised Learning Models for Sensor-based Human Activity Recognition—0
Continuous Human Activity Recognition using a MIMO Radar for Transitional Motion Analysis—0
WEAR: An Outdoor Sports Dataset for Wearable and Egocentric Activity RecognitionCode1
Domain Adaptation for Inertial Measurement Unit-based Human Activity Recognition: A Survey—0
Multi-Channel Time-Series Person and Soft-Biometric Identification—0
WSense: A Robust Feature Learning Module for Lightweight Human Activity RecognitionCode0
Hard Regularization to Prevent Deep Online Clustering Collapse without Data AugmentationCode0
Sensing with OFDM Waveform at mmWave Band based on Micro-Doppler Analysis—0
Channel Phase Processing in Wireless Networks for Human Activity Recognition—0
Time Series Segmentation Applied to a New Data Set for Mobile Sensing of Human ActivitiesCode1
Provable Robustness for Streaming Models with a Sliding Window—0
Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (VIDIMU)Code1
A Multi-Task Deep Learning Approach for Sensor-based Human Activity Recognition and Segmentation—0
Mobiprox: Supporting Dynamic Approximate Computing on Mobiles—0
Zone-based Federated Learning for Mobile Sensing Data—0
Sleep Quality Prediction from Wearables using Convolution Neural Networks and Ensemble Learning—0
Robust Multimodal Fusion for Human Activity Recognition—0
VALERIAN: Invariant Feature Learning for IMU Sensor-based Human Activity Recognition in the Wild—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
Towards Activated Muscle Group Estimation in the WildCode1
A Preliminary Study on Pattern Reconstruction for Optimal Storage of Wearable Sensor Data—0
On Handling Catastrophic Forgetting for Incremental Learning of Human Physical Activity on the Edge—0
cGAN-Based High Dimensional IMU Sensor Data Generation for Enhanced Human Activity Recognition in Therapeutic Activities—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