# rPPG-Toolbox: Deep Remote PPG Toolbox

arXiv: https://arxiv.org/abs/2210.00716 · HTML: https://mlsanity.com/paper/2210.00716/

## Key facts

- Cited by 64 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 69 references that are in the map.
- First posted on arXiv 3 Oct 2022.

## Builds on (most cited first, 25 of 25)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks](https://mlsanity.com/paper/1805.07888/) (2018)
- [Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement](https://mlsanity.com/paper/2006.03790/) (2020)
- [Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks](https://mlsanity.com/paper/1905.02419/) (2019)
- [PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer](https://mlsanity.com/paper/2111.12082/) (2021)
- [RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation](https://mlsanity.com/paper/1910.11515/) (2019)
- [Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement](https://mlsanity.com/paper/1907.11921/) (2019)
- [Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling](https://mlsanity.com/paper/2007.08213/) (2020)
- [EfficientPhys: Enabling Simple, Fast and Accurate Camera-Based Vitals Measurement](https://mlsanity.com/paper/2110.04447/) (2021)
- [The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video](https://mlsanity.com/paper/2111.09748/) (2021)
- [PulseGAN: Learning to generate realistic pulse waveforms in remote photoplethysmography](https://mlsanity.com/paper/2006.02699/) (2020)
- [Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner](https://mlsanity.com/paper/2007.06786/) (2020)
- [Camera Measurement of Physiological Vital Signs](https://mlsanity.com/paper/2111.11547/) (2021)
- [Contrast-Phys: Unsupervised Video-based Remote Physiological Measurement via Spatiotemporal Contrast](https://mlsanity.com/paper/2208.04378/) (2022)
- [Behavioral Use Licensing for Responsible AI](https://mlsanity.com/paper/2011.03116/) (2020)
- [TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection](https://mlsanity.com/paper/2104.07419/) (2021)
- [SCAMPS: Synthetics for Camera Measurement of Physiological Signals](https://mlsanity.com/paper/2206.04197/) (2022)
- [Analysis of CNN-based remote-PPG to understand limitations and sensitivities](https://mlsanity.com/paper/1911.02736/) (2019)
- [Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars](https://mlsanity.com/paper/2010.12949/) (2020)
- [Efficient Remote Photoplethysmography with Temporal Derivative Modules and Time-Shift Invariant Loss](https://mlsanity.com/paper/2203.10882/) (2022)
- [iPhys: An Open Non-Contact Imaging-Based Physiological Measurement Toolbox](https://mlsanity.com/paper/1901.04366/) (2019)
- [Assessment of deep learning based blood pressure prediction from PPG and rPPG signals](https://mlsanity.com/paper/2104.09313/) (2021)
- [Federated Remote Physiological Measurement with Imperfect Data](https://mlsanity.com/paper/2203.05759/) (2022)
- [On the Vector Space in Photoplethysmography Imaging](https://mlsanity.com/paper/1906.04431/) (2019)

## Built on by (most cited first, 30 of 64)

- [RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention](https://mlsanity.com/paper/2402.12788/) (2024)
- [Spiking-PhysFormer: Camera-Based Remote Photoplethysmography with Parallel Spike-driven Transformer](https://mlsanity.com/paper/2402.04798/) (2024)
- [PhysMamba: Efficient Remote Physiological Measurement with SlowFast Temporal Difference Mamba](https://mlsanity.com/paper/2409.12031/) (2024)
- [FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing](https://mlsanity.com/paper/2411.01542/) (2024)
- [BigSmall: Efficient Multi-Task Learning for Disparate Spatial and Temporal Physiological Measurements](https://mlsanity.com/paper/2303.11573/) (2023)
- [Motion Matters: Neural Motion Transfer for Better Camera Physiological Measurement](https://mlsanity.com/paper/2303.12059/) (2023)
- [egoPPG: Heart Rate Estimation from Eye-Tracking Cameras in Egocentric Systems to Benefit Downstream Vision Tasks](https://mlsanity.com/paper/2502.20879/) (2025)
- [How Suboptimal is Training rPPG Models with Videos and Targets from Different Body Sites?](https://mlsanity.com/paper/2403.10582/) (2024)
- [On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI](https://mlsanity.com/paper/2402.05979/) (2024)
- [PhysDrive: A Multimodal Remote Physiological Measurement Dataset for In-vehicle Driver Monitoring](https://mlsanity.com/paper/2507.19172/) (2025)
- [Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation](https://mlsanity.com/paper/2404.09378/) (2024)
- [Summit Vitals: Multi-Camera and Multi-Signal Biosensing at High Altitudes](https://mlsanity.com/paper/2409.19223/) (2024)
- [CalibrationPhys: Self-supervised Video-based Heart and Respiratory Rate Measurements by Calibrating Between Multiple Cameras](https://mlsanity.com/paper/2310.15043/) (2023)
- [Self-similarity Prior Distillation for Unsupervised Remote Physiological Measurement](https://mlsanity.com/paper/2311.05100/) (2023)
- [Camera-Based Remote Physiology Sensing for Hundreds of Subjects Across Skin Tones](https://mlsanity.com/paper/2404.05003/) (2024)
- [Gaze into the Heart: A Multi-View Video Dataset for rPPG and Health Biomarkers Estimation](https://mlsanity.com/paper/2508.17924/) (2025)
- [Semi-rPPG: Semi-Supervised Remote Physiological Measurement with Curriculum Pseudo-Labeling](https://mlsanity.com/paper/2502.03855/) (2025)
- [Non-Contact Health Monitoring During Daily Personal Care Routines](https://mlsanity.com/paper/2506.09718/) (2025)
- [Phase-shifted remote photoplethysmography for estimating heart rate and blood pressure from facial video](https://mlsanity.com/paper/2401.04560/) (2024)
- [Passive Heart Rate Monitoring During Smartphone Use in Everyday Life](https://mlsanity.com/paper/2503.03783/) (2025)
- [Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models](https://mlsanity.com/paper/2503.17269/) (2025)
- [Memory-efficient Low-latency Remote Photoplethysmography through Temporal-Spatial State Space Duality](https://mlsanity.com/paper/2504.01774/) (2025)
- [Robust and Generalizable Heart Rate Estimation via Deep Learning for Remote Photoplethysmography in Complex Scenarios](https://mlsanity.com/paper/2507.07795/) (2025)
- [BeatFormer: Efficient motion-robust remote heart rate estimation through unsupervised spectral zoomed attention filters](https://mlsanity.com/paper/2507.14885/) (2025)
- [Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods](https://mlsanity.com/paper/2401.04801/) (2024)
- [MHAD: Multimodal Home Activity Dataset with Multi-Angle Videos and Synchronized Physiological Signals](https://mlsanity.com/paper/2409.09366/) (2024)
- [Generalization of Video-Based Heart Rate Estimation Methods To Low Illumination and Elevated Heart Rates](https://mlsanity.com/paper/2503.11697/) (2025)
- [Editing Physiological Signals in Videos Using Latent Representations](https://mlsanity.com/paper/2509.25348/) (2025)
- [M3PD Dataset: Dual-view Photoplethysmography (PPG) Using Front-and-rear Cameras of Smartphones in Lab and Clinical Settings](https://mlsanity.com/paper/2511.02349/) (2025)
- [Quality-Aware Framework for Video-Derived Respiratory Signals](https://mlsanity.com/paper/2512.14093/) (2025)

## Abstract (arXiv)

Camera-based physiological measurement is a fast growing field of computer vision. Remote photoplethysmography (rPPG) utilizes imaging devices (e.g., cameras) to measure the peripheral blood volume pulse (BVP) via photoplethysmography, and enables cardiac measurement via webcams and smartphones. However, the task is non-trivial with important pre-processing, modeling, and post-processing steps required to obtain state-of-the-art results. Replication of results and benchmarking of new models is critical for scientific progress; however, as with many other applications of deep learning, reliable codebases are not easy to find or use. We present a comprehensive toolbox, rPPG-Toolbox, that contains unsupervised and supervised rPPG models with support for public benchmark datasets, data augmentation, and systematic evaluation: urlhttps://github.com/ubicomplab/rPPG-Toolbox