Unsupervised Image-To-Image Translation

49 papers with code • 2 benchmarks • 2 datasets

Unsupervised image-to-image translation is the task of doing image-to-image translation without ground truth image-to-image pairings.

( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )

Greatest papers with code

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

tensorflow/models ICCV 2017

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.

 Ranked #1 on Image-to-Image Translation on photo2vangogh (Frechet Inception Distance metric)

Multimodal Unsupervised Image-To-Image Translation Style Transfer +1

Unsupervised Image-to-Image Translation Networks

eriklindernoren/PyTorch-GAN NeurIPS 2017

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 +1

U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

taki0112/UGATIT ICLR 2020

We propose a novel method for unsupervised image-to-image translation, which incorporates a new attention module and a new learnable normalization function in an end-to-end manner.

Fundus to Angiography Generation Unsupervised Image-To-Image Translation

COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder

nvlabs/imaginaire ECCV 2020

Unsupervised image-to-image translation intends to learn a mapping of an image in a given domain to an analogous image in a different domain, without explicit supervision of the mapping.

Unsupervised Image-To-Image Translation

Unsupervised Cross-Domain Image Generation

kaonashi-tyc/zi2zi 7 Nov 2016

We study the problem of transferring a sample in one domain to an analog sample in another domain.

Domain Adaptation Unsupervised Image-To-Image Translation

Few-Shot Unsupervised Image-to-Image Translation

NVlabs/FUNIT ICCV 2019

Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets of images.

Unsupervised Image-To-Image Translation

Unsupervised Domain Adaptation by Backpropagation

thuml/Transfer-Learning-Library 26 Sep 2014

Here, we propose a new approach to domain adaptation in deep architectures that can be trained on large amount of labeled data from the source domain and large amount of unlabeled data from the target domain (no labeled target-domain data is necessary).

Image Classification Multi-target Domain Adaptation +3

Instance-aware Image-to-Image Translation

sangwoomo/instagan ICLR 2019

Unsupervised image-to-image translation has gained considerable attention due to the recent impressive progress based on generative adversarial networks (GANs).

Semantic Segmentation Unsupervised Image-To-Image Translation