arXiv Computer Vision
InscriptionOCR: A Dataset and Method for Understanding Inscriptions
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Aug 28
Ancient-Bench: A Comprehensive Multi-millennial, Multi-medium, and Multi-script Benchmark for Ancient Chinese Artifact Text Recognition
Ancient-Bench is a new benchmark for recognizing text on ancient Chinese artifacts, comprising 2,700 images that span 3,000 years of character evolution, nine artifact categories, and seven historical script forms. It introduces three annotation standards—symbol, character, and parsing standardization—to accommodate medium‑specific characteristics and enable consistent evaluation. Experiments show that current Vision‑Language Models and OCR specialists still struggle with variant characters, specialized symbols, and hallucination, indicating the task remains largely unsolved.
arXiv AI
Aug 20
Impact of Iterative Fine-Tuning on Transcription Accuracy in Complex Historical Sanskrit Manuscripts
The paper presents a local traditional OCR pipeline that can be iteratively fine‑tuned on both layout and appearance levels of complex historical Sanskrit manuscripts. By adapting to the specific manuscript distribution, the pipeline reduces human annotation effort and improves transcription accuracy across subsequent pages. The authors apply this method to three manuscripts, release a dataset with detailed layout and Unicode annotations in PAGE‑XML format, and benchmark the pipeline against leading multimodal large language models.
Hugging Face Trending Papers
Aug 19
Impact of Iterative Fine-Tuning on Transcription Accuracy in Complex Historical Sanskrit Manuscripts
The paper presents a local traditional OCR pipeline that can be iteratively fine‑tuned on both layout and appearance levels of complex historical Sanskrit manuscripts. By adapting to the specific manuscript distribution, the pipeline improves transcription accuracy across subsequent pages, reducing the need for costly human annotation. The authors apply the method to three manuscripts, release a dataset with detailed layout and Unicode annotations in PAGE‑XML format, and benchmark the results against leading multimodal large language models.
arXiv AI
Jul 23
Persian Pixel: A large-scale synthetic OCR dataset for Persian language
arXiv:2607. 20385v1 Announce Type: cross Abstract: Optical Character Recognition (OCR) for Persian remains substantially less mature than for Latin-script languages despite Persian being spoken by more than 110 million people across multiple countries.
arXiv Computer Vision
Sep 2
A Text Recognition Dataset from Sahidic Coptic Ancient Manuscripts
The paper introduces SCAM, a line-level dataset of digitized Sahidic Coptic ancient manuscripts designed for Handwritten Text Recognition in low-resource settings. SCAM captures realistic challenges such as varied acquisition conditions, ink fading, bleed-through, and material deterioration, while also presenting linguistic difficulties due to the scarce resources, uncommon alphabet, and dialect-specific diacritics of Sahidic Coptic. The authors benchmark several state‑of‑the‑art HTR methods, demonstrating the performance gap between modern, well‑resourced scripts and historically grounded, low‑resource scenarios.
arXiv AI
Aug 11
TongGuOCR: A Layout-Aware and Token-Augmented OCR Framework for Chinese Historical Documents
arXiv:2608. 07917v1 Announce Type: new Abstract: Chinese historical documents preserve valuable cultural heritage, but many collections remain accessible only as scanned page images, preventing full-text retrieval, collation, and computational analysis.