From db8fdfda9893de130e21ef770daffc5336942a9f Mon Sep 17 00:00:00 2001 From: Yi Yang Date: Sat, 4 Dec 2021 20:36:02 -0800 Subject: [PATCH 1/2] Update README.md Add two newer unsupervised / weakly-Supervised Deep Denoising methods. One is Noisy-as-clean in ITIP 2020 and another is self2self in CVPR2020. --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index a7ee47d..59d5fc6 100644 --- a/README.md +++ b/README.md @@ -100,6 +100,8 @@ Check out the following collections of reproducible state-of-the-art algorithms: * Noise2Self: Blind Denoising by Self-Supervision (ICML 2019), Batson and Royer * Self-Supervised Denoising [[Web]](https://github.com/NVlabs/selfsupervised-denoising) [[Code]](https://github.com/NVlabs/selfsupervised-denoising) [[PDF]](https://arxiv.org/abs/1901.10277) * High-Quality Self-Supervised Deep Image Denoising (NIPS 2019), Laine et al. + * Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image [[Web]](https://github.com/csjunxu/Noisy-As-Clean-TIP2020) [[PDF]](https://ieeexplore.ieee.org/document/9210208) + * Self2Self With Dropout: Learning Self-Supervised Denoising From Single Image [[Web]](https://openaccess.thecvf.com/content_CVPR_2020/html/Quan_Self2Self_With_Dropout_Learning_Self-Supervised_Denoising_From_Single_Image_CVPR_2020_paper.html) [[PDF]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Quan_Self2Self_With_Dropout_Learning_Self-Supervised_Denoising_From_Single_Image_CVPR_2020_paper.pdf) [[Code]](https://github.com/scut-mingqinchen/self2self) #### Hybrid Model for Denoising * STROLLR [[PDF]](http://transformlearning.csl.illinois.edu/assets/Bihan/ConferencePapers/BihanICASSP2017strollr.pdf) [[Code]](https://github.com/wenbihan/strollr2d_icassp2017) From d4cb9ef77dd897f26478274f34db1af077d87847 Mon Sep 17 00:00:00 2001 From: Yi Yang Date: Sat, 4 Dec 2021 20:37:32 -0800 Subject: [PATCH 2/2] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 59d5fc6..d8ce9b5 100644 --- a/README.md +++ b/README.md @@ -99,9 +99,9 @@ Check out the following collections of reproducible state-of-the-art algorithms: * Noise2Self [[Web]](https://github.com/czbiohub/noise2self) [[Code]](https://github.com/czbiohub/noise2self) [[PDF]](https://arxiv.org/abs/1811.10980) * Noise2Self: Blind Denoising by Self-Supervision (ICML 2019), Batson and Royer * Self-Supervised Denoising [[Web]](https://github.com/NVlabs/selfsupervised-denoising) [[Code]](https://github.com/NVlabs/selfsupervised-denoising) [[PDF]](https://arxiv.org/abs/1901.10277) - * High-Quality Self-Supervised Deep Image Denoising (NIPS 2019), Laine et al. - * Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image [[Web]](https://github.com/csjunxu/Noisy-As-Clean-TIP2020) [[PDF]](https://ieeexplore.ieee.org/document/9210208) - * Self2Self With Dropout: Learning Self-Supervised Denoising From Single Image [[Web]](https://openaccess.thecvf.com/content_CVPR_2020/html/Quan_Self2Self_With_Dropout_Learning_Self-Supervised_Denoising_From_Single_Image_CVPR_2020_paper.html) [[PDF]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Quan_Self2Self_With_Dropout_Learning_Self-Supervised_Denoising_From_Single_Image_CVPR_2020_paper.pdf) [[Code]](https://github.com/scut-mingqinchen/self2self) +* High-Quality Self-Supervised Deep Image Denoising (NIPS 2019), Laine et al. +* Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image [[Web]](https://github.com/csjunxu/Noisy-As-Clean-TIP2020) [[PDF]](https://ieeexplore.ieee.org/document/9210208) +* Self2Self With Dropout: Learning Self-Supervised Denoising From Single Image [[Web]](https://openaccess.thecvf.com/content_CVPR_2020/html/Quan_Self2Self_With_Dropout_Learning_Self-Supervised_Denoising_From_Single_Image_CVPR_2020_paper.html) [[Code]](https://github.com/scut-mingqinchen/self2self) #### Hybrid Model for Denoising * STROLLR [[PDF]](http://transformlearning.csl.illinois.edu/assets/Bihan/ConferencePapers/BihanICASSP2017strollr.pdf) [[Code]](https://github.com/wenbihan/strollr2d_icassp2017)