Search Results for author: Roee Litman

Found 9 papers, 3 papers with code

Can You Read Me Now? Content Aware Rectification using Angle Supervision

no code implementations ECCV 2020 Amir Markovitz, Inbal Lavi, Or Perel, Shai Mazor, Roee Litman

We present CREASE: Content Aware Rectification using Angle Supervision, the first learned method for document rectification that relies on the document's content, the location of the words and specifically their orientation, as hints to assist in the rectification process.

Optical Character Recognition

SCATTER: Selective Context Attentional Scene Text Recognizer

1 code implementation CVPR 2020 Ron Litman, Oron Anschel, Shahar Tsiper, Roee Litman, Shai Mazor, R. Manmatha

The first attention step re-weights visual features from a CNN backbone together with contextual features computed by a BiLSTM layer.

Irregular Text Recognition Scene Text Recognition

ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation

3 code implementations CVPR 2020 Sharon Fogel, Hadar Averbuch-Elor, Sarel Cohen, Shai Mazor, Roee Litman

This is especially true for handwritten text recognition (HTR), where each author has a unique style, unlike printed text, where the variation is smaller by design.

Domain Adaptation Handwriting generation +3

Latent RANSAC

1 code implementation CVPR 2018 Simon Korman, Roee Litman

We present a method that can evaluate a RANSAC hypothesis in constant time, i. e. independent of the size of the data.

3D Face Alignment 3D Plane Detection +4

Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space

no code implementations CVPR 2017 Matthias Vestner, Roee Litman, Emanuele Rodolà, Alex Bronstein, Daniel Cremers

Many algorithms for the computation of correspondences between deformable shapes rely on some variant of nearest neighbor matching in a descriptor space.

Density Estimation

Bayesian Inference of Bijective Non-Rigid Shape Correspondence

no code implementations12 Jul 2016 Matthias Vestner, Roee Litman, Alex Bronstein, Emanuele Rodolà, Daniel Cremers

Many algorithms for the computation of correspondences between deformable shapes rely on some variant of nearest neighbor matching in a descriptor space.

Bayesian Inference

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