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Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–275 of 744 papers

TitleStatusHype
Eco-Friendly Sensing for Human Activity Recognition—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
Effective Human Activity Recognition Based on Small Datasets—0
Layer-wise training convolutional neural networks with smaller filters for human activity recognition using wearable sensors—0
"Filling the Blanks'': Identifying Micro-activities that Compose Complex Human Activities of Daily Living—0
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models—0
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications—0
DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understanding—0
Post-train Black-box Defense via Bayesian Boundary Correction—0
Attention-Based Sensor Fusion for Human Activity Recognition Using IMU Signals—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—0
Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors—0
Deep Transfer Learning for Cross-domain Activity Recognition—0
Attend And Discriminate: Beyond the State-of-the-Art for Human Activity Recognition using Wearable Sensors—0
Maximum Likelihood Speed Estimation of Moving Objects in Video Signals—0
Activity Recognition in Assembly Tasks by Bayesian Filtering in Multi-Hypergraphs—0
Deep Recurrent Neural Network for Mobile Human Activity Recognition with High Throughput—0
Deep Positive Unlabeled Learning with a Sequential Bias—0
Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances—0
A Tiny Supervised ODL Core with Auto Data Pruning for Human Activity Recognition—0
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities—0
A systematic review of smartphone-based human activity recognition for health research—0
Deep Learning for Computer Vision based Activity Recognition and Fall Detection of the Elderly: a Systematic Review—0
AsyMov: Integrated Sensing and Communications with Asynchronous Moving Devices—0
A Masked Semi-Supervised Learning Approach for Otago Micro Labels 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