SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 426–450 of 744 papers

TitleStatusHype
Ultra-compact Binary Neural Networks for Human Activity Recognition on RISC-V ProcessorsCode0
A Wireless-Vision Dataset for Privacy Preserving Human Activity Recognition—0
UMSNet: An Universal Multi-sensor Network for Human Activity Recognition—0
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
Resource-Eficient Continual Learning for Sensor-Based Human Activity Recognition—0
A Close Look into Human Activity Recognition Models using Deep Learning—0
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptationCode0
EfficientFi: Towards Large-Scale Lightweight WiFi Sensing via CSI Compression—0
SecureSense: Defending Adversarial Attack for Secure Device-Free Human Activity Recognition—0
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition—0
Seeker: Synergizing Mobile and Energy Harvesting Wearable Sensors for Human Activity Recognition—0
EnHDC: Ensemble Learning for Brain-Inspired Hyperdimensional Computing—0
Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—0
Lifelong Adaptive Machine Learning for Sensor-based Human Activity Recognition Using Prototypical Networks—0
Defending Black-box Skeleton-based Human Activity ClassifiersCode0
Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity RecognitionCode0
LSTMSPLIT: Effective SPLIT Learning based LSTM on Sequential Time-Series Data—0
Assessing the State of Self-Supervised Human Activity Recognition using Wearables—0
MuMu: Cooperative Multitask Learning-based Guided Multimodal Fusion—0
CROMOSim: A Deep Learning-based Cross-modality Inertial Measurement Simulator—0
Integrated Human Activity Sensing and Communications—0
FLAME: Federated Learning Across Multi-device Environments—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