NaviDC-OCR: Navigating Document Parsing Across Digital and Camera-Captured Documents

• URL: http://arxiv.org/abs/2608.12898v2
• Date: Tue, 18 Aug 2026 06:14:21 GMT
• Title: NaviDC-OCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• Abstract summary: We propose NaviDC-OCR, a unified framework for document parsing.<n> NaviDC-OCR introduces deformation-aware learning to incorporate geometric perception into VLMs.<n>It achieves state-of-the-art performance across diverse document parsing benchmarks.
• Score: 18.60763757268658
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Document parsing aims to transform unstructured documents into structured and machine-readable representations. Recent advances in Vision-Language Models (VLMs) have significantly advanced document parsing. However, existing approaches still face two major challenges. First, decoupled VLM-based methods heavily rely on accurate layout analysis, where geometric distortions in camera-captured documents can introduce cascading errors. Second, although end-to-end VLM-based methods alleviate the dependence on explicit layout detection, they often suffer from redundant generation, hallucinations, and insufficient structural reasoning in high-resolution scenarios. To address these challenges, we propose NaviDC-OCR, a unified framework for document parsing. NaviDC-OCR introduces deformation-aware learning to incorporate geometric perception into VLMs and proposes an adaptive sampling mechanism for complex layout representation. Furthermore, a content-structure decoupled learning strategy is developed to explicitly model formula grammars and table structures, enabling more effective structured representation learning. Extensive experiments demonstrate that NaviDC-OCR achieves state-of-the-art performance across diverse document parsing benchmarks. It obtains overall scores of 96.87, 88.53 and 78.41 on OmniDocBench v1.6, Wild-OmniDocBench, and PureDocBench, respectively, and ranks first in the ICDAR 2026 Sci-ImageMiner Challenge. These results validate the effectiveness and generalization capability of NaviDC-OCR in complex document parsing scenarios.

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