papers

Publications (9)

cs.CV2022

TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers

Oren Nuriel, Sharon Fogel, Ron Litman

Leveraging the characteristics of convolutional layers, neural networks are extremely effective for pattern recognition tasks. However in some cases, their decisions are based on u…

cs.CV2021

Single Pair Cross-Modality Super Resolution

Guy Shacht, Sharon Fogel, Dov Danon +2

Non-visual imaging sensors are widely used in the industry for different purposes. Those sensors are more expensive than visual (RGB) sensors, and usually produce images with lower…

cs.CV2018

Clustering-driven Deep Embedding with Pairwise Constraints

Sharon Fogel, Hadar Averbuch-Elor, Jacov Goldberger +1

Recently, there has been increasing interest to leverage the competence of neural networks to analyze data. In particular, new clustering methods that employ deep embeddings have b…

cs.CV2019

Blind Visual Motif Removal from a Single Image

Amir Hertz, Sharon Fogel, Rana Hanocka +2

Many images shared over the web include overlaid objects, or visual motifs, such as text, symbols or drawings, which add a description or decoration to the image. For example, deco…

cs.GR2019

PointWise: An Unsupervised Point-wise Feature Learning Network

Matan Shoef, Sharon Fogel, Daniel Cohen-Or

We present a novel approach to learning a point-wise, meaningful embedding for point-clouds in an unsupervised manner, through the use of neural-networks. The domain of point-cloud…

cs.CV2025

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

Ofir Abramovich, Niv Nayman, Sharon Fogel +7

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 mo…