Font Recognition
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Benchmarks
Most implemented
Texture or Semantics? Vision-Language Models Get Lost in Font Recognition
Combining OCR Models for Reading Early Modern Printed Books
HENet: Forcing a Network to Think More for Font Recognition
Character-independent font identification
Learning Typographic Style
Papers
Texture or Semantics? Vision-Language Models Get Lost in Font Recognition
Modern Vision-Language Models (VLMs) exhibit remarkable visual and linguistic capabilities, achieving impressive performance in various tasks such as image recognition and object localization. However, their effectivenes…
Few-Shot LearningFont RecognitionObject LocalizationMMR: Evaluating Reading Ability of Large Multimodal Models
Large multimodal models (LMMs) have demonstrated impressive capabilities in understanding various types of image, including text-rich images. Most existing text-rich image benchmarks are simple extraction-based question …
Font RecognitionMMR totalOptical Character Recognition (OCR)Question Answering+2Total Disentanglement of Font Images into Style and Character Class Features
In this paper, we demonstrate a total disentanglement of font images. Total disentanglement is a neural network-based method for decomposing each font image nonlinearly and completely into its style and content (i.e., ch…
DisentanglementFont RecognitionImage GenerationPersis: A Persian Font Recognition Pipeline Using Convolutional Neural Networks
What happens if we encounter a suitable font for our design work but do not know its name? Visual Font Recognition (VFR) systems are used to identify the font typeface in an image. These systems can assist graphic design…
BinarizationCPUFont RecognitionGPU+2Combining OCR Models for Reading Early Modern Printed Books
In this paper, we investigate the usage of fine-grained font recognition on OCR for books printed from the 15th to the 18th century. We used a newly created dataset for OCR of early printed books for which fonts are labe…
Font RecognitionOptical Character Recognition (OCR)HENet: Forcing a Network to Think More for Font Recognition
Although lots of progress were made in Text Recognition/OCR in recent years, the task of font recognition is remaining challenging. The main challenge lies in the subtle difference between these similar fonts, which is h…
Font RecognitionOptical Character Recognition (OCR)