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Found 11 papers, 1 papers with code
Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity
Domain shift differences between training data for deep learning models and the deployment context can result in severe performance issues for models which fail to generalize.
MSPM: A Multi-Site Physiological Monitoring Dataset for Remote Pulse, Respiration, and Blood Pressure Estimation
We provide thorough experiments demonstrating the suitability of MSPM to support research on rPPG, respiration rate, and PTT.
Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods
Model architecture refinement is a challenging task in deep learning research fields such as remote photoplethysmography (rPPG).
Promoting Generalization in Cross-Dataset Remote Photoplethysmography
Remote Photoplethysmography (rPPG), or the remote monitoring of a subject's heart rate using a camera, has seen a shift from handcrafted techniques to deep learning models.
Full-Body Cardiovascular Sensing with Remote Photoplethysmography
In this paper we explored the feasibility of rPPG from non-face body regions such as the arms, legs, and hands.
Non-Contrastive Unsupervised Learning of Physiological Signals from Video
Given the limited inductive biases and impressive empirical results, the approach is theoretically capable of discovering other periodic signals from video, enabling multiple physiological measurements without the need for ground truth signals.
Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation
Extensive experimentation with eight research datasets (rPPG-specific: DDPM, CDDPM, PURE, UBFC, ARPM; deep fakes: DFDC; face presentation attack detection: HKBU-MARs; rPPG outlier: KITTI) show better accuracy of anomaly detection for deep learning models incorporating the proposed training (75. 8%), compared to models trained regularly (73. 7%) and to hand-crafted rPPG methods (52-62%).
Digital and Physical-World Attacks on Remote Pulse Detection
Remote photoplethysmography (rPPG) is a technique for estimating blood volume changes from reflected light without the need for a contact sensor.
Deception Detection and Remote Physiological Monitoring: A Dataset and Baseline Experimental Results
Our application context is an interview scenario in which the interviewee attempts to deceive the interviewer on selected responses.
Remote Pulse Estimation in the Presence of Face Masks
Remote photoplethysmography (rPPG), a family of techniques for monitoring blood volume changes, may be especially useful for widespread contactless health monitoring using face video from consumer-grade visible-light cameras.
An Online Reinforcement Learning Approach to Quality-Cost-Aware Task Allocation for Multi-Attribute Social Sensing
Social sensing has emerged as a new sensing paradigm where humans (or devices on their behalf) collectively report measurements about the physical world.
