Fundus to Angiography Generation

8 papers with code • 1 benchmarks • 0 datasets

Generating Retinal Fluorescein Angiography from Retinal Fundus Image using Generative Adversarial Networks.


Greatest papers with code

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

taki0112/UGATIT 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.

 Ranked #1 on Image-to-Image Translation on cat2dog (Kernel Inception Distance metric)

Fundus to Angiography Generation Unsupervised Image-To-Image Translation

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

NVIDIA/pix2pixHD CVPR 2018

We present a new method for synthesizing high-resolution photo-realistic images from semantic label maps using conditional generative adversarial networks (conditional GANs).

Conditional Image Generation Fundus to Angiography Generation +2

StarGAN v2: Diverse Image Synthesis for Multiple Domains

clovaai/stargan-v2 CVPR 2020

A good image-to-image translation model should learn a mapping between different visual domains while satisfying the following properties: 1) diversity of generated images and 2) scalability over multiple domains.

Fundus to Angiography Generation Multimodal Unsupervised Image-To-Image Translation