作者
Joao C Neves, Ruben Tolosana, Ruben Vera-Rodriguez, Vasco Lopes, Hugo Proença, Julian Fierrez
发表日期
2020
期刊
IEEE Journal of Selected Topics in Signal Processing
简介
The availability of large-scale facial databases, together with the remarkable progresses of deep learning technologies, in particular Generative Adversarial Networks (GANs), have led to the generation of extremely realistic fake facial content, raising obvious concerns about the potential for misuse. Such concerns have fostered the research on manipulation detection methods that, contrary to humans, have already achieved astonishing results in various scenarios. In this study, we focus on the synthesis of entire facial images, which is a specific type of facial manipulation. The main contributions of this study are four-fold: i) a novel strategy to remove GAN “fingerprints” from synthetic fake images based on autoencoders is described, in order to spoof facial manipulation detection systems while keeping the visual quality of the resulting images; ii) an in-depth analysis of the recent literature in facial manipulation …
学术搜索中的文章
JC Neves, R Tolosana, R Vera-Rodriguez, V Lopes… - IEEE Journal of Selected Topics in Signal Processing, 2020
JC Neves, R Tolosana, R Vera-Rodriguez, V Lopes… - arXiv preprint arXiv:1911.05351, 2019