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# PaperEdge
The code and the DIW dataset for "Learning From Documents in the Wild to Improve Document Unwarping" (SIGGRAPH 2022)
![image](https://user-images.githubusercontent.com/12742725/177686793-77c6652e-f86a-45ea-829f-78306f2d5021.png)
## Documents In the Wild (DIW) dataset (2.13GB)
[link](https://drive.google.com/file/d/1qAmLurt6bK0ro8PnRz6rBgVs1rfrsdKi/view?usp=sharing)
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[docunet_benchmark_paperedge.zip](https://drive.google.com/file/d/1QM3Y5Ty96ydVCQPNqR0_bnMG9oqIQkGm/view?usp=sharing)
The last row of `adres.txt` is the evaluation results.
The values in the last 3 columns are `AD`, `MS-SSIM`, and `LD`.
The values in the last 3 columns are `AD`, `MS-SSIM`, and `LD`.