Browse > Computer Vision > Image-to-Image Translation > Multimodal Unsupervised Image-To-Image Translation

Multimodal Unsupervised Image-To-Image Translation

4 papers with code · Computer Vision

Multimodal unsupervised image-to-image translation is the task of producing multiple translations to one domain from a single image in another domain.

State-of-the-art leaderboards

Greatest papers with code

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

ICCV 2017 tensorflow/models

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.

MULTIMODAL UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION STYLE TRANSFER UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Multimodal Unsupervised Image-to-Image Translation

ECCV 2018 nvlabs/MUNIT

To translate an image to another domain, we recombine its content code with a random style code sampled from the style space of the target domain.

MULTIMODAL UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Unsupervised Image-to-Image Translation Networks

NeurIPS 2017 mingyuliutw/UNIT

Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains.

DOMAIN ADAPTATION MULTIMODAL UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION