From 655a8ef9f0e37be3a09c2502fd9f80af5224386e Mon Sep 17 00:00:00 2001 From: Zhaozixiang1228 <44187438+Zhaozixiang1228@users.noreply.github.com> Date: Tue, 18 Jul 2023 09:43:42 +0200 Subject: [PATCH] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 8dc2e74..888feaf 100644 --- a/README.md +++ b/README.md @@ -32,11 +32,11 @@ Multi-modality (MM) image fusion aims to render fused images that maintain the m ## Usage -### Network Architecture +### ⚙ Network Architecture Our CDDFuse is implemented in ``net.py``. -### Training +### 🏊 Training **1. Virtual Environment** ``` # create virtual environment @@ -67,7 +67,7 @@ python train.py ``` and the trained model is available in ``'./models/'``. -### Testing +### 🏄 Testing **1. Pretrained models** @@ -136,7 +136,7 @@ CDDFuse_MIF 3.9 58.31 20.87 2.49 1.35 0.97 0.78 1.48 ``` which can match the results in Table 5 in our original paper. -## CDDFuse +## 🙌 CDDFuse ### Illustration of our CDDFuse model. @@ -169,7 +169,7 @@ MM segmentation -## Related Work +## 📖 Related Work - Zixiang Zhao, Haowen Bai, Jiangshe Zhang, Yulun Zhang, Kai Zhang, Shuang Xu, Dongdong Chen, Radu Timofte, Luc Van Gool. *Equivariant Multi-Modality Image Fusion.* **arXiv:2305.11443**, https://arxiv.org/abs/2305.11443