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-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 Image-to-Image Translation on Cityscapes Photo-to-Labels
Recently, with the revolutionary neural style transferring methods, creditable paintings can be synthesized automatically from content images and style images.
We consider image transformation problems, where an input image is transformed into an output image.
#5 best model for Nuclear Segmentation on Cell17
This note presents an extension to the neural artistic style transfer algorithm (Gatys et al.).
Gatys et al. recently demonstrated that deep networks can generate beautiful textures and stylized images from a single texture example.