mlsanityData to 7 Oct 2026

Digital and Physical-World Attacks on Remote Pulse Detection

arXiv 2110.11525 ↗First posted 21 Oct 2021cs.CV cs.LGcited by 3

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Abstract (arXiv)

Remote photoplethysmography (rPPG) is a technique for estimating blood volume changes from reflected light without the need for a contact sensor. We present the first examples of presentation attacks in the digital and physical domains on rPPG from face video. Digital attacks are easily performed by adding imperceptible periodic noise to the input videos. Physical attacks are performed with illumination from visible spectrum LEDs placed in close proximity to the face, while still being difficult to perceive with the human eye. We also show that our attacks extend beyond medical applications, since the method can effectively generate a strong periodic pulse on 3D-printed face masks, which presents difficulties for pulse-based face presentation attack detection (PAD). The paper concludes with ideas for using this work to improve robustness of rPPG methods and pulse-based face PAD.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 14 of its 39 references that are in the map. First posted on arXiv 21 Oct 2021.

Builds on

14 of 39 references.

References · 14

  1. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  2. 2013Intriguing properties of neural networkscited by 5,114
  3. 2016Adversarial examples in the physical worldcited by 1,762
  4. 2017One pixel attack for fooling deep neural networkscited by 579
  5. 2018DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networkscited by 153
  6. 2019Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networkscited by 126
  7. 2019RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representationcited by 104
  8. 2019Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancementcited by 86
  9. 2020Video-based Remote Physiological Measurement via Cross-verified Feature Disentanglingcited by 78
  10. 2020DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythmscited by 65
  11. 2020Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learnercited by 58
  12. 2020How Do the Hearts of Deep Fakes Beat? Deep Fake Source Detection via Interpreting Residuals with Biological Signalscited by 29
2 more
  1. 2020DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimationcited by 28
  2. 2021Deception Detection and Remote Physiological Monitoring: A Dataset and Baseline Experimental Resultscited by 16

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Citing papers per year: 2023: 2; 2024: 1.

3 papers.