Science Score: 67.0%

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    Found 1 DOI reference(s) in README
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    Links to: ieee.org
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Repository

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  • Host: GitHub
  • Owner: wangsen99
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 1.6 MB
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Created over 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection

This repo is the official implementation of "CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection (IEEE TIP 2024)".

Installation

``` conda create -n md python=3.7 -y conda activate md

conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=11.0 -c pytorch pip install mmcv-full==1.4.0 -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.1/index.html

cd CSFwinformer

pip install -e . pip install -r requirements/optional.txt

mkdir data

```

Data Preparation

"MSD"

"PMD"

"RGBD-Mirror"

You can download zip files for corresponding three datasets from "here"

Train

python tools/train.py configs/mirror/pmd_mirror_swin_small.py

Test

python ./tools/test.py configs/mirror/pmd_mirror_swin_small.py work_dirs/pmd_mirror_swin_small/your_weight --show-dir ./results/pmd --eval mIoU

Results and Models

| Dataset | Backbone| IoU↑ | Acc↑ | $Fβ$↑ | MAE↓ | BER↓ | | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | PMD | swins | 69.84 | 77.28 | 0.849 | 0.024 | 11.91 | | PMD | swinb | 70.05 | 78.27 | 0.838 | 0.024 | 11.41 | | MSD | swins | 82.13 | 88.72 | 0.895 | 0.046 | 7.15 | | MSD | swinb | 82.08 | 88.92 | 0.896 | 0.045 | 7.14 | | RGBD-Mirror | swinb | 78.66 | 84.64 | 0.900 | 0.031 | 8.57 |

You can find all weights from "here"

Citation

If you find this repo useful for your research, please consider citing our paper: @ARTICLE{10462920, author={Xie, Zhifeng and Wang, Sen and Yu, Qiucheng and Tan, Xin and Xie, Yuan}, journal={IEEE Transactions on Image Processing}, title={CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection}, year={2024}, volume={33}, number={}, pages={1853-1867}, keywords={Mirrors;Feature extraction;Transformers;Frequency-domain analysis;Visualization;Semantics;Image segmentation;Mirror detection;texture analysis;cross-modality learning;frequency learning}, doi={10.1109/TIP.2024.3372468}}

Owner

  • Login: wangsen99
  • Kind: user
  • Location: Earth

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - name: "MMSegmentation Contributors"
title: "OpenMMLab Semantic Segmentation Toolbox and Benchmark"
date-released: 2020-07-10
url: "https://github.com/open-mmlab/mmsegmentation"
license: Apache-2.0

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