Stars
Trying out PyTorch Lightning with a Blood Pressure predictor from PPG
Assessment of non-invasive blood pressure prediction from PPG and rPPG signals using deep learning
Deep learning framework for accurate blood pressure (BP) estimation from PPG signals. Features include signal selection & enhancement, dual-path temporal/image-based feature extraction, M-SCAN atte…
Accurately predict blood pressure in real-time by integrating features from multiple wearable sensor signal channels with just a few seconds of input signal.
Generalizable Deep Learning for Photoplethysmography-Based Blood Pressure Estimation – A Benchmarking Study
Reconstructing blood pressure waves from imaging photoplethysmographic signals
This is the code corresponding to the paper "Resolve Domain Conflicts for Generalizable Remote Physiological Measurement." accepted in ACM MM 2023.
[TPAMI & ECCV 2022] Contrast-Phys & Contrast-Phys+ for facial video-based remote physiological signal measurement
Multi-Modal Multi-Task Remote Physiological Sensing
rPPG-Toolbox: Deep Remote PPG Toolbox (NeurIPS 2023)
ME-rPPG is a memory-efficient realtime rPPG network
Open-source implementation for estimating vital signs from facial videos using remote photoplethysmography
The source code of "SFDA-rPPG: Source-free Domain Adaptive rPPG Measurement with Spatial-Temporal Consistency"
FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing [NeurIPS 2024]
[CVPRW2024] Repository for the paper "Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation"
This is the official code repository of our IEEE FG 2024 paper "RS-rPPG: Robust Self-Supervised Learning for rPPG" and IEEE TCSVT paper "RS+rPPG: Robust Strongly Self-Supervised Learning for rPPG"
Official code of IEEE TIM "Generalizable Remote Physiological Measurement via Semantic-Sheltered Alignment and Plausible Style Randomization"
Camera-based heart rate prediction using deep learning and signal processing with real-time rPPG from video. Modular, GPU-compatible, and ready for telehealth or fitness integration.