Fundus to Angiography Generation
6 papers with code • 1 benchmarks • 0 datasets
Generating Retinal Fluorescein Angiography from Retinal Fundus Image using Generative Adversarial Networks.
Benchmarks
These leaderboards are used to track progress in Fundus to Angiography Generation
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Most implemented papers
Image-to-Image Translation with Conditional Adversarial Networks
phillipi/pix2pix
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CVPR 2017
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
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.
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
NVIDIA/pix2pixHD
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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).
StarGAN v2: Diverse Image Synthesis for Multiple Domains
clovaai/stargan-v2
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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.
0-Step Capturability, Motion Decomposition and Global Feedback Control of the 3D Variable Height-Inverted Pendulum
We also prove that the 3D VHIP with Fixed CoP is the same as its 2D version, and we generalize controllers working on the 2D VHIP to the 3D VHIP.
VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers
Tinysqua/VTGAN-pytorch-version
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The only non-invasive method for capturing retinal vasculature is optical coherence tomography-angiography (OCTA).
