Font Recognition
6 papers with code • 8 benchmarks • 9 datasets
Font recognition (also called visual font recognition or optical font recognition) is the task of identifying the font family or families used in images containing text. Understanding which fonts are used in text may, for example, help designers find the right style, as well as help select an optical character recognition engine or model that is a better fit for certain texts.
Benchmarks
These leaderboards are used to track progress in Font Recognition
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Datasets
Explor_all
AdobeVFR syn
Persian Font Recognition (PFR)
Persian Text Image Segmentation (PTI SEG)
Dafonts Free
Most implemented papers
DeepFont: Identify Your Font from An Image
As font is one of the core design concepts, automatic font identification and similar font suggestion from an image or photo has been on the wish list of many designers.
Learning Typographic Style
Typography is a ubiquitous art form that affects our understanding, perception, and trust in what we read.
Character-independent font identification
PhamQuocHuy1101/Character-independent-font-identification
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Moreover, we analyzed the relationship between character classes and font identification accuracy.
HENet: Forcing a Network to Think More for Font Recognition
PhamQuocHuy1101/transfer-learning-template
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Although lots of progress were made in Text Recognition/OCR in recent years, the task of font recognition is remaining challenging.
Persis: A Persian Font Recognition Pipeline Using Convolutional Neural Networks
Visual Font Recognition (VFR) systems are used to identify the font typeface in an image.
Combining OCR Models for Reading Early Modern Printed Books
Moreover, we developed a system using local font group recognition in order to combine the output of multiple font recognition models, and show that while slower, this approach performs better not only on text lines composed of multiple fonts but on the ones containing a single font only as well.
