SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

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Showing 351–400 of 744 papers

TitleStatusHype
Millimeter Wave Radar-based Human Activity Recognition for Healthcare Monitoring Robot—0
Mobiprox: Supporting Dynamic Approximate Computing on Mobiles—0
A Light-weight Deep Human Activity Recognition Algorithm Using Multi-knowledge Distillation—0
Unleashing the Power of Shared Label Structures for Human Activity Recognition—0
Modelling the Influence of Cultural Information on Vision-Based Human Home Activity Recognition—0
MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition—0
MORIC: CSI Delay-Doppler Decomposition for Robust Wi-Fi-based Human Activity Recognition—0
Motion Classification using Kinematically Sifted ACGAN-Synthesized Radar Micro-Doppler Signatures—0
MuJo: Multimodal Joint Feature Space Learning for Human Activity Recognition—0
Multi-channel Time Series Decomposition Network For Generalizable Sensor-Based Activity Recognition—0
Multi-Channel Time-Series Person and Soft-Biometric Identification—0
Multidimensional Human Activity Recognition With Large Language Model: A Conceptual Framework—0
Multi-GAT: A Graphical Attention-based Hierarchical Multimodal Representation Learning Approach for Human Activity Recognition—0
Multi-label Class-imbalanced Action Recognition in Hockey Videos via 3D Convolutional Neural Networks—0
Multi-label Prediction in Time Series Data using Deep Neural Networks—0
Multi-level Contrast Network for Wearables-based Joint Activity Segmentation and Recognition—0
Multimodal Contrastive Learning with Hard Negative Sampling for Human Activity Recognition—0
Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification—0
Multiple Human Association between Top and Horizontal Views by Matching Subjects' Spatial Distributions—0
Multi-Scale and Multi-Modal Contrastive Learning Network for Biomedical Time Series—0
Multi-Stage Based Feature Fusion of Multi-Modal Data for Human Activity Recognition—0
Multi-task Self-Supervised Learning for Human Activity Detection—0
Multivariate Time Series Classification Using Dynamic Time Warping Template Selection for Human Activity Recognition—0
Multi-View Fusion Transformer for Sensor-Based Human Activity Recognition—0
MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning—0
MuMu: Cooperative Multitask Learning-based Guided Multimodal Fusion—0
Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices—0
Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition—0
NERULA: A Dual-Pathway Self-Supervised Learning Framework for Electrocardiogram Signal Analysis—0
Neural Style Transfer Enhanced Training Support For Human Activity Recognition—0
Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition—0
New Convex Relaxations for MRF Inference With Unknown Graphs—0
Non-stationary BERT: Exploring Augmented IMU Data For Robust Human Activity Recognition—0
Object and Text-guided Semantics for CNN-based Activity Recognition—0
On Attention Models for Human Activity Recognition—0
On Handling Catastrophic Forgetting for Incremental Learning of Human Physical Activity on the Edge—0
To Store or Not? Online Data Selection for Federated Learning with Limited Storage—0
Online Human Activity Recognition Employing Hierarchical Hidden Markov Models—0
Online Human Activity Recognition using Low-Power Wearable Devices—0
On the Benefit of Generative Foundation Models for Human Activity Recognition—0
On the recognition of the game type based on physiological signals and eye tracking—0
OpenPack: A Large-scale Dataset for Recognizing Packaging Works in IoT-enabled Logistic Environments—0
Optimised Convolutional Neural Networks for Heart Rate Estimation and Human Activity Recognition in Wrist Worn Sensing Applications—0
Optimized Gated Deep Learning Architectures for Sensor Fusion—0
Otago Exercises Monitoring for Older Adults by a Single IMU and Hierarchical Machine Learning Models—0
Overview of Human Activity Recognition Using Sensor Data—0
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer—0
PALMAR: Towards Adaptive Multi-inhabitant Activity Recognition in Point-Cloud Technology—0
Past, Present, and Future of Sensor-Based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task—0
PerceptionNet: A Deep Convolutional Neural Network for Late Sensor Fusion—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