Dataset generation with GAN for reflection image removal on eyeglasses

Sota Watanabe; Makoto Hasegawa

doi:10.1117/12.2626935

30 April 2022 Dataset generation with GAN for reflection image removal on eyeglasses

Sota Watanabe, Makoto Hasegawa

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 1217722 (2022) https://doi.org/10.1117/12.2626935
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

This study investigated a method for removing display images reflected on eyeglasses with blue light-cutting lenses using deep learning. A dataset of images with and without reflections on eyeglasses was generated with an identical angle of view, and a U-net was trained on the generated dataset. The trained model removed reflections from images. In this study, not only the dataset consisting of actual images but also the above dataset was trained using a generative adversarial network (GAN) to generate a large number of images. By increasing the number of images in the dataset, the reflection removal accuracy was improved.

Citation Download Citation

Sota Watanabe and Makoto Hasegawa "Dataset generation with GAN for reflection image removal on eyeglasses", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 1217722 (30 April 2022); https://doi.org/10.1117/12.2626935

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