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@@ -1,8 +1,10 @@
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# L-CNN — End-to-End Wireframe Parsing
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+This repository contains the official PyTorch implementation of the paper: *Yichao Zhou, Haozhi Qi, Yi Ma. ["End-to-End Wireframe Parsing."](https://arxiv.org/abs/1905.03246) arXiv:1905.03246 [cs.CV]*.
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+
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## Introduction
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-This repository contains the official PyTorch implementation of [L-CNN](https://arxiv.org/abs/1905.03246), a conceptually simple yet effective neural network-based algorithm for detecting the wireframe from a given image. It outperforms the previous state-of-the-art wireframe and line extraction algorithms by a large margin. We hope that this repository serves as an easily reproducible baseline for future researches in this area.
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+[L-CNN](https://arxiv.org/abs/1905.03246) is a conceptually simple yet effective neural network for detecting the wireframe from a given image. It outperforms the previous state-of-the-art wireframe and line detectors by a large margin. We hope that this repository serves as an easily reproducible baseline for future researches in this area.
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## Main Results
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@@ -14,7 +16,7 @@ This repository contains the official PyTorch implementation of [L-CNN](https://
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### Quantitative Measures
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-The following table reports the performance of several wireframe and line detection algorithms on the [Wireframe dataset](https://github.com/huangkuns/wireframe).
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+The following table reports the performance metrics of several wireframe and line detectors on the [Wireframe dataset](https://github.com/huangkuns/wireframe).
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| | Wireframe (sAP<sup>10</sup>) | Wireframe (AP<sup>H</sup>) | Wireframe (F<sup>H</sup>) | Wireframe (mAP<sup>J</sup>) |
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| :--------------------------------------------------: | :--------------------------------: | :-----------------------------: | :----------------------------: | :------------------------------: |
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@@ -63,6 +65,7 @@ eval-APH.py # script for APH evaluation
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eval-mAPJ.py # script for mAPJ evaluation
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train.py # script for training the neural network
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post.py # script for post-processing
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+process.py # script for processing a dataset from a checkpoint
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```
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## Reproducing Results
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@@ -93,7 +96,7 @@ rm *.xz
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cd ..
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```
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-If `gdrive-download.sh` does not work for you, you can download the data manually from [Google
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+If `gdrive-download.sh` does not work for you, you can download the pre-processed dataset manually from [Google
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Drive](https://drive.google.com/drive/u/1/folders/1rXLAh5VIj8jwf8vLfuZncStihRO2chFr) and proceed
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accordingly.
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Yichao Zhou