most citedOn Calibration of Scene-Text Recognition Models

1 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV20211 cited

Learning Multimodal Affinities for Textual Editing in Images

Or Perel, Oron Anschel, Omri Ben-Eliezer +2

Nowadays, as cameras are rapidly adopted in our daily routine, images of documents are becoming both abundant and prevalent. Unlike natural images that capture physical objects, do…

cs.CV20201 cited

On Calibration of Scene-Text Recognition Models

Ron Slossberg, Oron Anschel, Amir Markovitz +6

In this work, we study the problem of word-level confidence calibration for scene-text recognition (STR). Although the topic of confidence calibration has been an active research a…

cs.CV2020

Sequence-to-Sequence Contrastive Learning for Text Recognition

Aviad Aberdam, Ron Litman, Shahar Tsiper +5

We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition. To account for the sequence-to-sequence…

cs.CV2020

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

Amir Markovitz, Inbal Lavi, Or Perel +2

The ubiquity of smartphone cameras has led to more and more documents being captured by cameras rather than scanned. Unlike flatbed scanners, photographed documents are often folde…

cs.CV2020

SCATTER: Selective Context Attentional Scene Text Recognizer

Ron Litman, Oron Anschel, Shahar Tsiper +3

Scene Text Recognition (STR), the task of recognizing text against complex image backgrounds, is an active area of research. Current state-of-the-art (SOTA) methods still struggle…

cs.CV2020

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…