CycleGANによる形状変換を目的とした画像処理

抄録

CycleGAN is a technique that realizes image transformation by learning the relationship between the domains of two images. CycleGAN is good at style conversion such as color and pattern, but there is a problem that conversion accompanied by shape conversion is difficult. The reason is that CycleGAN recognizes the image background as part of the conversion target and cannot perform feature extraction well. In this research, shape transformation by CycleGAN is performed by preparing a data set in which the image background is deleted by a generative model.