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Image-to-Image Translation

93 papers with code · Computer Vision
Subtask of Image Generation

Image-to-image translation is the task of taking images from one domain and transforming them so they have the style (or characteristics) of images from another domain.

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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

Learning from Simulated and Unsupervised Images through Adversarial Training

CVPR 2017 tensorflow/models

With recent progress in graphics, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations.

GAZE ESTIMATION HAND POSE ESTIMATION IMAGE-TO-IMAGE TRANSLATION

DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

ICCV 2017 eriklindernoren/Keras-GAN

Depending on the task complexity, thousands to millions of labeled image pairs are needed to train a conditional GAN.

IMAGE-TO-IMAGE TRANSLATION

Coupled Generative Adversarial Networks

NeurIPS 2016 eriklindernoren/Keras-GAN

We propose coupled generative adversarial network (CoGAN) for learning a joint distribution of multi-domain images.

DOMAIN ADAPTATION IMAGE-TO-IMAGE TRANSLATION

Semantic Image Synthesis with Spatially-Adaptive Normalization

CVPR 2019 NVlabs/SPADE

We propose spatially-adaptive normalization, a simple but effective layer for synthesizing photorealistic images given an input semantic layout.

IMAGE-TO-IMAGE TRANSLATION

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

CVPR 2018 eriklindernoren/PyTorch-GAN

To address this limitation, we propose StarGAN, a novel and scalable approach that can perform image-to-image translations for multiple domains using only a single model.

 SOTA for Image-to-Image Translation on RaFD (using extra training data)

IMAGE-TO-IMAGE TRANSLATION

Unsupervised Image-to-Image Translation Networks

NeurIPS 2017 eriklindernoren/PyTorch-GAN

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