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Found 5 papers, 2 papers with code
DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression Networks
In this work, we propose DewarpNet, a deep-learning approach for document image unwarping from a single image.
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MS-SSIM
on DocUNet
(using extra training data)
Intrinsic Decomposition of Document Images In-the-Wild
However, document shadow or shading removal results still suffer because: (a) prior methods rely on uniformity of local color statistics, which limit their application on real-scenarios with complex document shapes and textures and; (b) synthetic or hybrid datasets with non-realistic, simulated lighting conditions are used to train the models.
End-to-End Piece-Wise Unwarping of Document Images
Document unwarping attempts to undo the physical deformation of the paper and recover a 'flatbed' scanned document-image for downstream tasks such as OCR.
Learning Surface Parameterization for Document Image Unwarping
We also demonstrate the usefulness of our system by applying it to document texture editing.
Automated Attribute Extraction from Legal Proceedings
The escalating number of pending cases is a growing concern world-wide.
