Using Fully Connected and Convolutional Net for GAN-Based Face Swapping

Bo Shue Lin, Ding Wen Hsu, Chin Han Shen, Hsu-Feng Hsiao

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

The lifelike results of using face swapping have contributed greatly to the research in computer vision. In this work, we extend the architecture of faceswap-GAN in order to obtain more natural results compared to the original framework. In the original architecture, the self-attention module usually converts the facial features from a source face to the target face with artificial distortion around the facial features. We use a structure of fully connected convolutional layers as a discriminator to approach the problem. The outcome can be smoother and more natural perceptually compared to the results using the original faceswap-GAN.

原文American English
主出版物標題Proceedings of 2020 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2020
編輯Xuan-Tu Tran, Duy-Hieu Bui
發行者Institute of Electrical and Electronics Engineers Inc.
頁面185-188
頁數4
ISBN(電子)9781728193960
DOIs
出版狀態Published - 8 12月 2020
事件16th IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2020 - Virtual, Halong, Viet Nam
持續時間: 8 12月 202010 12月 2020

出版系列

名字Proceedings of 2020 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2020

Conference

Conference16th IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2020
國家/地區Viet Nam
城市Virtual, Halong
期間8/12/2010/12/20

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