SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 576–600 of 744 papers

TitleStatusHype
EmbraceNet for Activity: A Deep Multimodal Fusion Architecture for Activity Recognition—0
Effective Human Activity Recognition Based on Small Datasets—0
Using GAN to Enhance the Accuracy of Indoor Human Activity Recognition—0
Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey—0
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables—0
Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention NetworksCode0
Optimised Convolutional Neural Networks for Heart Rate Estimation and Human Activity Recognition in Wrist Worn Sensing Applications—0
Simultaneous Learning from Human Pose and Object Cues for Real-Time Activity Recognition—0
Human Activity Recognition from Wearable Sensor Data Using Self-AttentionCode1
Adversarial Transferability in Wearable Sensor Systems—0
ActiLabel: A Combinatorial Transfer Learning Framework for Activity Recognition—0
A Fourier Domain Feature Approach for Human Activity Recognition & Fall Detection—0
Maximum Likelihood Speed Estimation of Moving Objects in Video Signals—0
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors—0
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery—0
Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework—0
Human Activity Recognition using Multi-Head CNN followed by LSTMCode0
Human Activity Recognition: A Spatio-temporal Image Encoding of 3D Skeleton Data for Online Action DetectionCode0
An Information-rich Sampling Technique over Spatio-Temporal CNN for Classification of Human Actions in Videos—0
Multi-label Prediction in Time Series Data using Deep Neural Networks—0
Are Accelerometers for Activity Recognition a Dead-end?—0
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities—0
Motion Classification using Kinematically Sifted ACGAN-Synthesized Radar Micro-Doppler Signatures—0
Personalized Activity Recognition with Deep Triplet EmbeddingsCode0
Classification of human activity recognition using smartphones—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