From 0132952fe32464d35b99057e1936933ce1c771fd Mon Sep 17 00:00:00 2001 From: "CVSM Group - email: czhu@bupt.edu.cn" <76641042+bupt-ai-cz@users.noreply.github.com> Date: Fri, 17 Sep 2021 11:22:40 +0800 Subject: [PATCH] Add papers --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index 1b1cbb5..cc80ae4 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,7 @@ The resources only focus on unsupervised domain adapation(UDA) and these include - [Unsupervised Domain Adaptation](#unsupervised-domain-adaptation) - [Conference Papers](#conference-papers) + - [2020 Conference Papers](#2020-conference-papers) - [2019 Conference Papers](#2019-conference-papers) - [2018 Conference Papers](#2018-conference-papers) - [Conference Papers befor 2018](#conference-papers-befor-2018) @@ -20,6 +21,8 @@ The resources only focus on unsupervised domain adapation(UDA) and these include ### 2020 Conference Papers | Abbreviation | Paper Title | Source Link | Code | Tags | | ------------ | ----------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | +| **IAST** | Instance Adaptive Self-Training for Unsupervised Domain Adaptation | [ECCV2020](https://arxiv.org/abs/2008.12197) | [Pytorch(Official)](https://github.com/bupt-ai-cz/IAST-ECCV2020) | `Self-training` | +| - | Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning | [ICASSP2020](https://arxiv.org/abs/2002.08587) | - | `Adversarial Training` `Medical` | | **MRNet** | Unsupervised Scene Adaptation with Memory Regularization in vivo | [IJCAI2019](https://arxiv.org/pdf/1912.11164.pdf) | [Pytorch(Official)](https://github.com/layumi/Seg-Uncertainty) | `Memory Regularization` | ### 2019 Conference Papers