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Sharon Fogel

7 accepted papers

2024

GRAM: Global Reasoning for Multi-Page VQA

CVPR 2024poster

The increasing use of transformer-based large language models brings forward the challenge of processing long sequences. In document visual question answering (DocVQA) leading methods focus on the single-page setting while documents can span hundreds of pages. We present GRAM a method that seamlessl…

Cited by 12SourcePDFScholar
2024

VisFocus: Prompt-Guided Vision Encoders for OCR-Free Dense Document Understanding

ECCV 2024poster

"In recent years, notable advancements have been made in the domain of visual document understanding, with the prevailing architecture comprising a cascade of vision and language models. The text component can either be extracted explicitly with the use of external OCR models in OCR-based approaches…

2022

TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers

ECCV 2022poster

"Leveraging the characteristics of convolutional layers, neural networks are extremely effective for pattern recognition tasks. However in some cases, their decisions are based on unintended information leading to high performance on standard benchmarks but also to a lack of generalization to challe…

2022

Towards Weakly-Supervised Text Spotting Using a Multi-Task Transformer

CVPR 2022poster

Text spotting end-to-end methods have recently gained attention in the literature due to the benefits of jointly optimizing the text detection and recognition components. Existing methods usually have a distinct separation between the detection and recognition branches, requiring exact annotations f…

Cited by 77PDFScholar
2020

ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation

CVPR 2020poster

Optical character recognition (OCR) systems performance have improved significantly in the deep learning era. 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. That said, deep learning…

Cited by 179PDFScholar