UDA-rPPG: Unsupervised Geometric-Physiological Domain Anchoring for Low-Light rPPG Measurement
Remote photoplethysmography (rPPG) is a critical technique for non-contact monitoring of human vital signs using facial video data. Most of the existing […]
Learning from Yourself to Others for Unsupervised Visible-Infrared Re-Identification
Unsupervised visible-infrared person re-identification (US-VI-ReID) aims to match unlabeled pedestrian images captured under varying lighting conditions. The key challenge lies in generating […]
ST-Phys: Unsupervised Spatio-Temporal Contrastive Remote Physiological Measurement
Remote photoplethysmography (rPPG) is a non-contact method that employs facial videos for measuring physiological parameters. Existing rPPG methods have achieved remarkable performance. […]
Unsupervised Learning-Based Joint Power Control and Fronthaul Capacity Allocation in Cell-Free Massive MIMO With Hardware Impairments
A deep learning-based resource allocation algorithm that maximizes the sum rate of a limited fronthaul cell-free massive MIMO network with transceiver hardware […]
Contrast-Phys
Video-based remote physiological measurement utilizes face videos to measure the blood volume change signal which is also called remote photoplethysmography (rPPG). Supervised […]
Deep ladder reconstruction-classification network for unsupervised domain adaptation
Unsupervised Domain Adaptation aims to learn a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain. Most […]
Joint Clustering and Discriminative Feature Alignment for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to learn a classifier for the unlabeled target domain by leveraging knowledge from a labeled source domain […]
Deep Learning-based Power Control for Cell-Free Massive MIMO Networks
A deep learning (DL)-based power control algorithm that solves the max-min user fairness problem in a cell-free massive multiple-input multiple-output (MIMO) system […]
Informative Feature Disentanglement for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims at learning a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain […]
Deep Ladder-Suppression Network for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims at learning a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain […]