International Display Workshops General Incorporated Association

11:05 〜 11:30

[AIS3/VHF5-2(Invited)] Improving Material Translation Based on Style Image Retrieval for Neural Style Transfer

*Gibran Benitez-Garcia1, Keiji Yanai2 (1. OMRON SINIC X Corp (Japan), 2. The University of Electro-Communications (Japan))

style image retrieval, material translation, neural style transfer

https://doi.org/10.36463/idw.2020.0981

In this talk, we introduce a CNN-feature-based image retrieval method to find the ideal style image that better translates the material of an object. We segment objects from the content image by using a weakly supervised segmentation method, and transfer the material of the retrieved style image to the segmented areas. With this method, we achieve realistic images that can even fool human perception.