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Human Activity Recognition

Classify various human activities

Papers

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Showing 326–350 of 744 papers

TitleStatusHype
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning—0
Explaining, Analyzing, and Probing Representations of Self-Supervised Learning Models for Sensor-based Human Activity Recognition—0
Generalization Ability Analysis of Through-the-Wall Radar Human Activity Recognition—0
Out-of-Distribution Representation Learning for Time Series Classification—0
A distillation-based approach integrating continual learning and federated learning for pervasive services—0
Human Activity Recognition for Mobile Robot—0
GeXSe (Generative Explanatory Sensor System): An Interpretable Deep Generative Model for Human Activity Recognition in Smart Spaces—0
Contrastive Left-Right Wearable Sensors (IMUs) Consistency Matching for HAR—0
GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes—0
Guided-GAN: Adversarial Representation Learning for Activity Recognition with Wearables—0
Hadamard Domain Training with Integers for Class Incremental Quantized Learning—0
HAMLET: A Hierarchical Multimodal Attention-based Human Activity Recognition Algorithm—0
ARC-Net: Activity Recognition Through Capsules—0
Explainable Deep Learning Framework for Human Activity Recognition—0
HAR-DoReMi: Optimizing Data Mixture for Self-Supervised Human Activity Recognition Across Heterogeneous IMU Datasets—0
CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition—0
Expanding Frozen Vision-Language Models without Retraining: Towards Improved Robot Perception—0
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network—0
HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?—0
CROMOSim: A Deep Learning-based Cross-modality Inertial Measurement Simulator—0
HAR-Net:Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition—0
Evolving Markov Chains: Unsupervised Mode Discovery and Recognition from Data Streams—0
Heterogeneous Relationships of Subjects and Shapelets for Semi-supervised Multivariate Series Classification—0
Cheating off your neighbors: Improving activity recognition through corroboration—0
A Comprehensive Methodological Survey of Human Activity Recognition Across Divers Data Modalities—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