Browse > Computer Vision > Image Generation > Image-to-Image Translation

Image-to-Image Translation Edit

126 papers with code · Computer Vision

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.

CalliGAN: Style and Structure-aware Chinese Calligraphy Character Generator

26 May 2020

Chinese calligraphy is the writing of Chinese characters as an art form performed with brushes so Chinese characters are rich of shapes and details.

CPOT: Channel Pruning via Optimal Transport

21 May 2020

Recent advances in deep neural networks (DNNs) lead to tremendously growing network parameters, making the deployments of DNNs on platforms with limited resources extremely difficult.

Medical Image Generation using Generative Adversarial Networks

19 May 2020

Generative adversarial networks (GANs) are unsupervised Deep Learning approach in the computer vision community which has gained significant attention from the last few years in identifying the internal structure of multimodal medical imaging data.

Synthetic Image Augmentation for Damage Region Segmentation using Conditional GAN with Structure Edge

7 May 2020

We propose a synthetic augmentation procedure to generate damaged images using the image-to-image translation mapping from the tri-categorical label that consists the both semantic label and structure edge to the real damage image.

DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation

6 May 2020

Promising results are shown for the tasks of color transfer, image colorization and edges $\rightarrow$ photo, where the color distribution of the output image is controlled.

StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching

5 May 2020

Large-scale synthetic datasets are beneficial to stereo matching but usually introduce known domain bias.

Improving Endoscopic Decision Support Systems by Translating Between Imaging Modalities

27 Apr 2020

We investigate if models can be trained on virtual (or a mixture of virtual and real) samples to improve overall accuracy in a setting with limited labeled training data.

Desmoking laparoscopy surgery images using an image-to-image translation guided by an embedded dark channel

19 Apr 2020

In laparoscopic surgery, the visibility in the image can be severely degraded by the smoke caused by the $CO_2$ injection, and dissection tools, thus reducing the visibility of organs and tissues.

TriGAN: Image-to-Image Translation for Multi-Source Domain Adaptation

19 Apr 2020

In this paper we propose the first approach for Multi-Source Domain Adaptation (MSDA) based on Generative Adversarial Networks.

Data-driven Flood Emulation: Speeding up Urban Flood Predictions by Deep Convolutional Neural Networks

17 Apr 2020

Computational complexity has been the bottleneck of applying physically-based simulations on large urban areas with high spatial resolution for efficient and systematic flooding analyses and risk assessments.