SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–700 of 744 papers

TitleStatusHype
Can Ensemble of Classifiers Provide Better Recognition Results in Packaging Activity?—0
Can You Spot the Semantic Predicate in this Video?—0
CDFL: Efficient Federated Human Activity Recognition using Contrastive Learning and Deep Clustering—0
cGAN-Based High Dimensional IMU Sensor Data Generation for Enhanced Human Activity Recognition in Therapeutic Activities—0
Channel Phase Processing in Wireless Networks for Human Activity Recognition—0
CHARM: A Hierarchical Deep Learning Model for Classification of Complex Human Activities Using Motion Sensors—0
Cheating off your neighbors: Improving activity recognition through corroboration—0
Self-supervised New Activity Detection in Sensor-based Smart Environments—0
Classification of human activity recognition using smartphones—0
Classifying Human Activities using Machine Learning and Deep Learning Techniques—0
Classifying Human Activities with Inertial Sensors: A Machine Learning Approach—0
CMD-HAR: Cross-Modal Disentanglement for Wearable Human Activity Recognition—0
CNN Autoencoders for Hierarchical Feature Extraction and Fusion in Multi-sensor Human Activity Recognition—0
CODA: A COst-efficient Test-time Domain Adaptation Mechanism for HAR—0
Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field—0
ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition—0
Comparative Analysis of XGBoost and Minirocket Algortihms for Human Activity Recognition—0
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables—0
Contact-Free Multi-Target Tracking Using Distributed Massive MIMO-OFDM Communication System: Prototype and Analysis—0
Contactless Human Activity Recognition using Deep Learning with Flexible and Scalable Software Define Radio—0
Context-driven Active and Incremental Activity Recognition—0
ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models—0
Contextual Relationship-based Activity Segmentation on an Event Stream in the IoT Environment with Multi-user Activities—0
Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization—0
Continual Learning in Sensor-based Human Activity Recognition: an Empirical Benchmark Analysis—0
Continuous Human Activity Recognition using a MIMO Radar for Transitional Motion Analysis—0
Contrastive Left-Right Wearable Sensors (IMUs) Consistency Matching for HAR—0
Contrastive Predictive Coding for Human Activity Recognition—0
ConViViT -- A Deep Neural Network Combining Convolutions and Factorized Self-Attention for Human Activity Recognition—0
CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition—0
Creating a Large-scale Synthetic Dataset for Human Activity Recognition—0
CROMOSim: A Deep Learning-based Cross-modality Inertial Measurement Simulator—0
Cross-Country Skiing Gears Classification using Deep Learning—0
Cross-domain Activity Recognition via Substructural Optimal Transport—0
Cross-Domain HAR: Few Shot Transfer Learning for Human Activity Recognition—0
Cross-position Activity Recognition with Stratified Transfer Learning—0
Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks—0
Cross-user activity recognition using deep domain adaptation with temporal relation information—0
Cross-user activity recognition via temporal relation optimal transport—0
CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community—0
CSI-Based Cross-Domain Activity Recognition via Zero-Shot Prototypical Networks—0
CSI-Based Efficient Self-Quarantine Monitoring System Using Branchy Convolution Neural Network—0
DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors—0
Dataset Bias in Human Activity Recognition—0
Decoding Human Activities: Analyzing Wearable Accelerometer and Gyroscope Data for Activity Recognition—0
Deep Activity Recognition Models with Triaxial Accelerometers—0
Deep Adaptive Temporal Pooling for Activity Recognition—0
Deep Adversarial Learning with Activity-Based User Discrimination Task for Human Activity Recognition—0
Deep, Convolutional, and Recurrent Models for Human Activity Recognition using Wearables—0
Deep Generative Domain Adaptation with Temporal Relation Knowledge for Cross-User Activity 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