SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 376–400 of 744 papers

TitleStatusHype
Unsupervised explainable activity prediction in competitive Nordic Walking from experimental data—0
Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition—0
Using GAN to Enhance the Accuracy of Indoor Human Activity Recognition—0
Utility-aware Privacy-preserving Data Releasing—0
VaCDA: Variational Contrastive Alignment-based Scalable Human Activity Recognition—0
VALERIAN: Invariant Feature Learning for IMU Sensor-based Human Activity Recognition in the Wild—0
VCHAR:Variance-Driven Complex Human Activity Recognition framework with Generative Representation—0
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition—0
Video2IMU: Realistic IMU features and signals from videos—0
Video-based Pose-Estimation Data as Source for Transfer Learning in Human Activity Recognition—0
Virtual Fusion with Contrastive Learning for Single Sensor-based Activity Recognition—0
Visual Recognition by Counting Instances: A Multi-Instance Cardinality Potential Kernel—0
ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos—0
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data—0
Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables—0
Wearable-based behaviour interpolation for semi-supervised human activity recognition—0
Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach—0
WiFi-based Spatiotemporal Human Action Perception—0
Wi-Motion: A Robust Human Activity Recognition Using WiFi Signals—0
XAI-BayesHAR: A novel Framework for Human Activity Recognition with Integrated Uncertainty and Shapely Values—0
X-Fi: A Modality-Invariant Foundation Model for Multimodal Human Sensing—0
Yet it moves: Learning from Generic Motions to Generate IMU data from YouTube videos—0
Your Day in Your Pocket: Complex Activity Recognition from Smartphone Accelerometers—0
ZKP-FedEval: Verifiable and Privacy-Preserving Federated Evaluation using Zero-Knowledge Proofs—0
Zone-based Federated Learning for Mobile Sensing Data—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