collaborators

6 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

PaddleOCR-VL-1.5: Towards a Multi-Task 0.9B VLM for Robust In-the-Wild Document Parsing

Cheng Cui, Ting Sun, Suyin Liang +12

We introduce PaddleOCR-VL-1.5, an upgraded model achieving a new state-of-the-art (SOTA) accuracy of 94.5% on OmniDocBench v1.5. To rigorously evaluate robustness against real-worl…

cs.CV2026

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…

cs.CV2025

PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model

Cheng Cui, Ting Sun, Suyin Liang +15

In this report, we propose PaddleOCR-VL, a SOTA and resource-efficient model tailored for document parsing. Its core component is PaddleOCR-VL-0.9B, a compact yet powerful vision-l…

cs.CV2025

PaddleOCR 3.0 Technical Report

Cheng Cui, Ting Sun, Manhui Lin +16

This technical report introduces PaddleOCR 3.0, an Apache-licensed open-source toolkit for OCR and document parsing. To address the growing demand for document understanding in the…