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Remote photoplethysmography (rPPG) is a non-contact method for detecting physiological signals based on facial videos, holding high potential in various applications.
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2023
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X. Liu, G. Narayanswamy, A. Paruchuri, X. Zhang, J. Tang, Y. Zhang, S. Sengupta, S. Patel, Y. Wang, D. McDuff, rPPG-toolbox: Deep remote PPG toolbox , in: Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2023. URL https://openreview.net/forum?id=q4XNX15kSe
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J. Li, Z. Yu, J. Shi, Learning motion-robust remote photoplethysmography through arbitrary resolution videos, in: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37, 2023, pp. 1334–1342
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Z. Li, L. Yin, Contactless pulse estimation leveraging pseudo labels and self-supervision, in: 2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 20531–20540 · 2023
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Z. Sun, X. Li, Contrast-phys+: Unsupervised and weakly-supervised video-based remote physiological measurement via spatiotemporal contrast, IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (8) (2024) 5835–5851 · 2024
Closest in time.
M. Liu, J. Tang, H. Li, J. Qi, S. Li, K. Wang, Y. Wang, H. Chen, Spiking-physformer: Camera-based remote photoplethysmography with parallel spike-driven transformer (2024) · 2024
Closest in time.
X. Liu, Y. Zhang, Z. Yu, H. Lu, H. Yue, J. Yang, rppg-mae: Self-supervised pretraining with masked autoencoders for remote physiological measurements, IEEE Transactions on Multimedia (2024)
2024
Closest in time.
Y. Zhang, H. Lu, X. Liu, Y. Chen, K. Wu, Advancing generalizable remote physiological measurement through the integration of explicit and implicit prior knowledge (2025) · 2025
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