Reproduce “OCR in the Foundation Model Era: From Specialist Models to Unified Models” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Zhiheng Li, Zongyang Ma, Jiaxian Chen, Cheng Cui, Yi Liu, Ziqi Zhang, Chunfeng Yuan, Bing Li and 2 more
The authors survey OCR systems that reconstruct visible text, notation, and document structure from images. They distinguish faithful transcription from question answering and organize systems into five families spanning specialist pipelines, whole-page models, hybrid workflows, general-purpose VLMs, and commercial services. On OmniDocBench v1.6 full, TeleOCR scores 96.91 Overall, while OvisOCR2 scores 96.47. The comparison does not establish a generally superior architecture.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.