no code implementations • 7 Jan 2024 • Tsachi Blau, Sharon Fogel, Roi Ronen, Alona Golts, Roy Ganz, Elad Ben Avraham, Aviad Aberdam, Shahar Tsiper, Ron Litman
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences.
no code implementations • CVPR 2022 • Yair Kittenplon, Inbal Lavi, Sharon Fogel, Yarin Bar, R. Manmatha, Pietro Perona
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.
1 code implementation • 9 May 2021 • Oren Nuriel, Sharon Fogel, Ron Litman
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 challenging testing conditions and unintuitive failures.
no code implementations • CVPR 2021 • Guy Shacht, Sharon Fogel, Dov Danon, Daniel Cohen-Or, Ilya Leizerson
The network is trained on the two input images only, learns their internal statistics and correlations, and applies them to up-sample the target modality.
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.
1 code implementation • CVPR 2019 • Amir Hertz, Sharon Fogel, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
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.
1 code implementation • 22 Mar 2018 • Sharon Fogel, Hadar Averbuch-Elor, Jacov Goldberger, Daniel Cohen-Or
In this paper, we depart from centroid-based models and suggest a new framework, called Clustering-driven deep embedding with PAirwise Constraints (CPAC), for non-parametric clustering using a neural network.