Image-to-Image Translation
490 papers with code • 37 benchmarks • 29 datasets
Image-to-Image Translation is a task in computer vision and machine learning where the goal is to learn a mapping between an input image and an output image, such that the output image can be used to perform a specific task, such as style transfer, data augmentation, or image restoration.
( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )
Benchmarks
These leaderboards are used to track progress in Image-to-Image Translation
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Libraries
Use these libraries to find Image-to-Image Translation models and implementationsDatasets
Cityscapes
KITTI
ADE20K
CelebA-HQ
SYNTHIA
GTA5
DeepFashion
Perceptual Similarity
AFHQ
COCO-Stuff
Subtasks
Most implemented papers
Learning to Adapt Structured Output Space for Semantic Segmentation
wasidennis/AdaptSegNet
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CVPR 2018
In this paper, we propose an adversarial learning method for domain adaptation in the context of semantic segmentation.
Joint Discriminative and Generative Learning for Person Re-identification
layumi/Person_reID_baseline_pytorch
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CVPR 2019
To this end, we propose a joint learning framework that couples re-id learning and data generation end-to-end.
Taming Transformers for High-Resolution Image Synthesis
CompVis/taming-transformers
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CVPR 2021
We demonstrate how combining the effectiveness of the inductive bias of CNNs with the expressivity of transformers enables them to model and thereby synthesize high-resolution images.
Multimodal Token Fusion for Vision Transformers
huawei-noah/noah-research
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journal 2022
Many adaptations of transformers have emerged to address the single-modal vision tasks, where self-attention modules are stacked to handle input sources like images.
Few-Shot Unsupervised Image-to-Image Translation
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.
Contrastive Learning for Unpaired Image-to-Image Translation
taesungp/contrastive-unpaired-translation
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Furthermore, we draw negatives from within the input image itself, rather than from the rest of the dataset.
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
eladrich/pixel2style2pixel
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CVPR 2021
We present a generic image-to-image translation framework, pixel2style2pixel (pSp).
Adversarially Learned Inference
We introduce the adversarially learned inference (ALI) model, which jointly learns a generation network and an inference network using an adversarial process.
Learning from Simulated and Unsupervised Images through Adversarial Training
carpedm20/simulated-unsupervised-tensorflow
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CVPR 2017
With recent progress in graphics, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations.
Unsupervised Image-to-Image Translation Networks
mingyuliutw/UNIT
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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.
