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

Unsupervised Image-To-Image Translation

24 papers with code ยท Computer Vision

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 )

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Latest papers without code

GMM-UNIT: Unsupervised Multi-Domain and Multi-Modal Image-to-Image Translation via Attribute Gaussian Mixture Modelling

ICLR 2020

Unsupervised image-to-image translation aims to learn a mapping between several visual domains by using unpaired training pairs.

UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

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

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.

UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Adversarial Self-Defense for Cycle-Consistent GANs

NeurIPS 2019

The goal of unsupervised image-to-image translation is to map images from one domain to another without the ground truth correspondence between the two domains.

ADVERSARIAL ATTACK UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

An Efficient Multi-Domain Framework for Image-to-Image Translation

28 Nov 2019

Existing approaches have been proposed to tackle unsupervised image-to-image translation in recent years.

UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Closing the Reality Gap with Unsupervised Sim-to-Real Image Translation for Semantic Segmentation in Robot Soccer

4 Nov 2019

Deep learning approaches have become the standard solution to many problems in computer vision and robotics, but obtaining proper and sufficient training data is often a problem, as human labor is often error prone, time consuming and expensive.

SEMANTIC SEGMENTATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Few-Shot Unsupervised Image-to-Image Translation

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

Mocycle-GAN: Unpaired Video-to-Video Translation

26 Aug 2019

Unsupervised image-to-image translation is the task of translating an image from one domain to another in the absence of any paired training examples and tends to be more applicable to practical applications.

MOTION ESTIMATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Latent Filter Scaling for Multimodal Unsupervised Image-To-Image Translation

CVPR 2019

In multimodal unsupervised image-to-image translation tasks, the goal is to translate an image from the source domain to many images in the target domain.

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

TransGaGa: Geometry-Aware Unsupervised Image-To-Image Translation

CVPR 2019

Extensive experiments demonstrate the superior performance of our method to other state-of-the-art approaches, especially in the challenging near-rigid and non-rigid objects translation tasks.

UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection

31 May 2019

In this context, Generative Adversarial Networks (GANs) can synthesize realistic/diverse additional training images to fill the data lack in the real image distribution; researchers have improved classification by augmenting data with noise-to-image (e. g., random noise samples to diverse pathological images) or image-to-image GANs (e. g., a benign image to a malignant one).

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