13 citations · 14 across the 2 of their papers we have counts for
6 papers
Towards Weakly-Supervised Text Spotting using a Multi-Task Transformer
Yair Kittenplon, Inbal Lavi, Sharon Fogel +3
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…
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…
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
Sharon Fogel, Hadar Averbuch-Elor, Sarel Cohen +2
Optical character recognition (OCR) systems performance have improved significantly in the deep learning era. This is especially true for handwritten text recognition (HTR), where…
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…
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…
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…