Style transfer is the task of changing the style of an image in one domain to the style of an image in another domain.
( Image credit: A Neural Algorithm of Artistic Style )
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.
#2 best model for Multimodal Unsupervised Image-To-Image Translation on EPFL NIR-VIS
Recently, with the revolutionary neural style transferring methods, creditable paintings can be synthesized automatically from content images and style images.
It this paper we revisit the fast stylization method introduced in Ulyanov et.
This note presents an extension to the neural artistic style transfer algorithm (Gatys et al.).
Binary classifiers are often employed as discriminators in GAN-based unsupervised style transfer systems to ensure that transferred sentences are similar to sentences in the target domain.