April 10, 2024, 4:45 a.m. | Bochao Zou, Zizheng Guo, Xiaocheng Hu, Huimin Ma

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.06483v1 Announce Type: new
Abstract: Remote photoplethysmography (rPPG) is a non-contact method for detecting physiological signals from facial videos, holding great potential in various applications such as healthcare, affective computing, and anti-spoofing. Existing deep learning methods struggle to address two core issues of rPPG simultaneously: extracting weak rPPG signals from video segments with large spatiotemporal redundancy and understanding the periodic patterns of rPPG among long contexts. This represents a trade-off between computational complexity and the ability to capture long-range dependencies, …

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