From b7c263b8c8f201a9123921d83dfe9bd73b38ec0c Mon Sep 17 00:00:00 2001 From: Xintao Date: Sat, 15 Jun 2019 00:49:00 +0800 Subject: [PATCH] Update README.md --- README.md | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index a5e5776..69fd41d 100644 --- a/README.md +++ b/README.md @@ -1,15 +1,21 @@ -# ESRGAN (Enhanced SRGAN) [[Paper]](https://arxiv.org/abs/1809.00219) [[BasicSR]](https://github.com/xinntao/BasicSR) +## ESRGAN (Enhanced SRGAN) [[BasicSR]](https://github.com/xinntao/BasicSR) [[EDVR]](https://github.com/xinntao/EDVR) [[DNI]](https://xinntao.github.io/projects/DNI) ### :smiley: Training codes are in [BasicSR](https://github.com/xinntao/BasicSR) repo. We have simplified the network structure file.
You can convert the previously save models (`*.pth`) with the script `transer_RRDB_models.py`;
If you want to use the old arch, you can find it [here](https://github.com/xinntao/ESRGAN/releases/tag/old-arch). + +--- +Check out our new work on:
+1. **Video Super-Resolution**: [`EDVR: Video Restoration with Enhanced Deformable Convolutional Networks`](https://xinntao.github.io/projects/EDVR), which has won all four tracks in NTIRE 2019 Challenges on Video Restoration and Enhancement (CVPR19 Workshops). +2. **DNI (CVPR19)**: [`Deep Network Interpolation for Continuous Imagery Effect Transition`](https://xinntao.github.io/projects/DNI) +--- + + ### Enhanced Super-Resolution Generative Adversarial Networks By Xintao Wang, [Ke Yu](https://yuke93.github.io/), Shixiang Wu, [Jinjin Gu](http://www.jasongt.com/), Yihao Liu, [Chao Dong](https://scholar.google.com.hk/citations?user=OSDCB0UAAAAJ&hl=en), [Yu Qiao](http://mmlab.siat.ac.cn/yuqiao/), [Chen Change Loy](http://personal.ie.cuhk.edu.hk/~ccloy/) -This repo only provides simple testing codes, pretrained models and the network strategy demo. - -### **For full training and testing codes, please refer to [BasicSR](https://github.com/xinntao/BasicSR).** +This repo only provides simple testing codes, pretrained models and the network strategy demo. For full training and testing codes, please refer to [BasicSR](https://github.com/xinntao/BasicSR). We won the first place in [PIRM2018-SR competition](https://www.pirm2018.org/PIRM-SR.html) (region 3) and got the best perceptual index. The paper is accepted to [ECCV2018 PIRM Workshop](https://pirm2018.org/). @@ -53,7 +59,7 @@ The **RRDB_PSNR** PSNR_oriented model trained with DF2K dataset (a merged datase ## Quick Test #### Dependencies - Python 3 -- [PyTorch >= 0.4](https://pytorch.org/) (CUDA version >= 7.5 if installing with CUDA. [More details](https://pytorch.org/get-started/previous-versions/)) +- [PyTorch >= 1.0](https://pytorch.org/) (CUDA version >= 7.5 if installing with CUDA. [More details](https://pytorch.org/get-started/previous-versions/)) - Python packages: `pip install numpy opencv-python` ### Test models