SOTAVerified

Human Activity Recognition

Classify various human activities

Papers

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Showing 701–744 of 744 papers

TitleStatusHype
Deep Generative Domain Adaptation with Temporal Attention for Cross-User Activity Recognition—0
Deep Learning for Computer Vision based Activity Recognition and Fall Detection of the Elderly: a Systematic Review—0
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities—0
Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances—0
Deep Positive Unlabeled Learning with a Sequential Bias—0
Deep Recurrent Neural Network for Mobile Human Activity Recognition with High Throughput—0
Deep Transfer Learning for Cross-domain Activity Recognition—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—0
Post-train Black-box Defense via Bayesian Boundary Correction—0
DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understanding—0
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications—0
Device-Free Human State Estimation using UWB Multi-Static Radios—0
DFTerNet: Towards 2-bit Dynamic Fusion Networks for Accurate Human Activity Recognition—0
DGAR: A Unified Domain Generalization Framework for RF-Enabled Human Activity Recognition—0
DIAT-μ RadHAR (micro-doppler signature dataset) & μ RadNet (a lightweight DCNN)—For human suspicious activity recognition—0
DIAT-RadHARNet: A lightweight DCNN for radar based classification of human suspicious activities—0
Different Approaches for Human Activity Recognition: A Survey—0
Differentiable Frequency-based Disentanglement for Aerial Video Action Recognition—0
DISC: a Dataset for Integrated Sensing and Communication in mmWave Systems—0
Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition—0
Disentangling Imperfect: A Wavelet-Infused Multilevel Heterogeneous Network for Human Activity Recognition in Flawed Wearable Sensor Data—0
Disparity-Augmented Trajectories for Human Activity Recognition—0
Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity Recognition—0
Distributed Agent-Based Collaborative Learning in Cross-Individual Wearable Sensor-Based Human Activity Recognition—0
Distribution estimation and change-point estimation for time series via DNN-based GANs—0
Diverse Intra- and Inter-Domain Activity Style Fusion for Cross-Person Generalization in Activity Recognition—0
DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization—0
DIVERSIFY to Generalize: Learning Generalized Representations for Time Series Classification—0
DNN Transfer Learning from Diversified Micro-Doppler for Motion Classification—0
Domain Adaptation for Inertial Measurement Unit-based Human Activity Recognition: A Survey—0
Domain-Adversarial Anatomical Graph Networks for Cross-User Human Activity Recognition—0
Domain Generalization for Activity Recognition via Adaptive Feature Fusion—0
Don't freeze: Finetune encoders for better Self-Supervised HAR—0
DroneAttention: Sparse Weighted Temporal Attention for Drone-Camera Based Activity Recognition—0
DS-MS-TCN: Otago Exercises Recognition with a Dual-Scale Multi-Stage Temporal Convolutional Network—0
Asymmetric Residual Neural Network for Accurate Human Activity Recognition—0
Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network—0
Dynamic Feature Selection for Efficient and Interpretable Human Activity Recognition—0
EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing—0
Early Improving Recurrent Elastic Highway Network—0
Early Mobility Recognition for Intensive Care Unit Patients Using Accelerometers—0
Eco-Friendly Sensing for Human Activity Recognition—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
Effective Human Activity Recognition Based on Small Datasets—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