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

Unsupervised Image-To-Image Translation

24 papers with code · 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 with code

Adversarial Self-Defense for Cycle-Consistent GANs

NeurIPS 2019 dbash/pix2pix_cyclegan_guess_noise

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

2
05 Aug 2019

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

25 Jul 2019taki0112/UGATIT

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

4,411
25 Jul 2019

Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night

19 Jul 2019LCAD-UFES/publications-arruda-ijcnn-2019

In this work, a method for training a car detection system with annotated data from a source domain (day images) without requiring the image annotations of the target domain (night images) is presented.

AUTONOMOUS VEHICLES OBJECT DETECTION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

9
19 Jul 2019

LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving

17 May 2019ahmadelsallab/lidargan

Simulators are often used for data augmentation, which requires realistic sensor models that are hard to formulate and model in closed forms.

AUTONOMOUS DRIVING DATA AUGMENTATION POINT CLOUD GENERATION SENSOR MODELING

2
17 May 2019

Few-Shot Unsupervised Image-to-Image Translation

ICCV 2019 NVlabs/FUNIT

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

1,101
05 May 2019

Instance-aware Image-to-Image Translation

ICLR 2019 sangwoomo/instagan

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

671
01 May 2019

Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation

28 Mar 2019Ha0Tang/AGGAN

To handle the limitation, in this paper we propose a novel Attention-Guided Generative Adversarial Network (AGGAN), which can detect the most discriminative semantic object and minimize changes of unwanted part for semantic manipulation problems without using extra data and models.

UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

126
28 Mar 2019

InstaGAN: Instance-aware Image-to-Image Translation

28 Dec 2018sangwoomo/instagan

Our comparative evaluation demonstrates the effectiveness of the proposed method on different image datasets, in particular, in the aforementioned challenging cases.

SEMANTIC SEGMENTATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

671
28 Dec 2018

Unsupervised Attention-guided Image-to-Image Translation

NeurIPS 2018 AlamiMejjati/Unsupervised-Attention-guided-Image-to-Image-Translation

Current unsupervised image-to-image translation techniques struggle to focus their attention on individual objects without altering the background or the way multiple objects interact within a scene.

UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

222
01 Dec 2018