7 papers
RT-DocLayout: Real-Time End-to-End Document Layout Analysis with Reading Order in the Wild
Cheng Cui, Tingquan Gao, Xueqing Wang +11
Accurate document layout analysis remains a critical bottleneck for document parsing systems, due to the intricate coupling among heterogeneous document layout elements, geometric…
Real5-OmniDocBench: A Full-Scale Physical Reconstruction Benchmark for Robust Document Parsing in the Wild
Changda Zhou, Ziyue Gao, Xueqing Wang +4
While Vision-Language Models (VLMs) achieve near-perfect scores on digital document benchmarks like OmniDocBench, their performance in the unpredictable physical world remains larg…
PP-OCRv6: From 1.5M to 34.5M Parameters, Surpassing Billion-Scale VLMs on OCR Tasks
Yubo Zhang, Xueqing Wang, Manhui Lin +13
Vision-Language Models (VLMs) have achieved impressive results on general vision-language tasks, yet they suffer from hallucination, imprecise localization, and prohibitive computa…
Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing
Cheng Cui, Ting Sun, Suyin Liang +15
Document parsing is a fine-grained task where image resolution significantly impacts performance. While advanced research leveraging vision-language models benefits from high-resol…
PP-OCRv5: A Specialized 5M-Parameter Model Rivaling Billion-Parameter Vision-Language Models on OCR Tasks
Cheng Cui, Yubo Zhang, Ting Sun +11
The advent of "OCR 2.0" and large-scale vision-language models (VLMs) has set new benchmarks in text recognition. However, these unified architectures often come with significant c…
PP-FormulaNet: Bridging Accuracy and Efficiency in Advanced Formula Recognition
Hongen Liu, Cheng Cui, Yuning Du +2
Formula recognition is an important task in document intelligence. It involves converting mathematical expressions from document images into structured symbolic formats that comput…