Search Results for author: Sagnik Das

Found 5 papers, 2 papers with code

Learning Surface Parameterization for Document Image Unwarping

no code implementations29 Sep 2021 Sagnik Das, Ke Ma, Zhixin Shu, Dimitris Samaras

We also demonstrate the usefulness of our system by applying it to document texture editing.

3D Scene Reconstruction

End-to-End Piece-Wise Unwarping of Document Images

no code implementations ICCV 2021 Sagnik Das, Kunwar Yashraj Singh, Jon Wu, Erhan Bas, Vijay Mahadevan, Rahul Bhotika, Dimitris Samaras

Document unwarping attempts to undo the physical deformation of the paper and recover a 'flatbed' scanned document-image for downstream tasks such as OCR.

MS-SSIM Optical Character Recognition (OCR) +1

Intrinsic Decomposition of Document Images In-the-Wild

1 code implementation29 Nov 2020 Sagnik Das, Hassan Ahmed Sial, Ke Ma, Ramon Baldrich, Maria Vanrell, Dimitris Samaras

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.

Document Shadow Removal Intrinsic Image Decomposition +1

DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression Networks

1 code implementation ICCV 2019 Sagnik Das, Ke Ma, Zhixin Shu, Dimitris Samaras, Roy Shilkrot

In this work, we propose DewarpNet, a deep-learning approach for document image unwarping from a single image.

 Ranked #1 on MS-SSIM on DocUNet (using extra training data)

Local Distortion MS-SSIM +3

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