计算机科学
人工智能
光容积图
背景(考古学)
语义学(计算机科学)
简单(哲学)
机器学习
计算机视觉
生物
滤波器(信号处理)
认识论
哲学
古生物学
程序设计语言
作者
Giuseppe Boccignone,Sathya Buršić,Vittorio Cuculo,Alessandro D’Amelio,Giuliano Grossi,Raffaella Lanzarotti,Sabrina Patania
标识
DOI:10.1007/978-3-031-06430-2_16
摘要
We present a simple, yet general method to detect fake videos displaying human subjects, generated via Deep Learning techniques. The method relies on gauging the complexity of heart rate dynamics as derived from the facial video streams through remote photoplethysmography (rPPG). Features analyzed have a clear semantics as to such physiological behaviour. The approach is thus explainable both in terms of the underlying context model and the entailed computational steps. Most important, when compared to more complex state-of-the-art detection methods, results so far achieved give evidence of its capability to cope with datasets produced by different deep fake models.
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