[CycleGAN] Unpaired image-to-image Translation using Cycle-Consistent Adversarial Networks
1. Abstract Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks, paired training data will not be available. We present an approach for learning to translate an image from a source domain X to a target domain Y in the absence of ..
Python/머신러닝&딥러닝 2020. 8. 18. 16:10