2019-11-08

Current focus:
1）DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks
2）MedGAN：Medical Image Translation using GANs
3）SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation
4）MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
5）Learning Fixed Points in Generative Adversarial Networks:From Image-to-Image Translation to Disease Detection and Localization
6）StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
7）Attention-guided Unified Network for Panoptic Segmentation
8）ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation
9） Multi-scale guided attention for medical image segmentation
10）Conditional Image-to-Image translation
11） Mix and match networks: encoder-decoder alignment for zero-pair image translation
12）Image to Image Translation for Domain Adaptation
13）f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks