TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
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 ...
| Authors | Peng Cai, Zhaofan Zou, Shifa Liu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 13 August 2026 |
| Last updated at source | 10 September 2026 |
Models and datasets referencing this paper
- XingChen-AGI/TeleOCRModel
- nandraj/NaviDC-OCR-GGUFModel
- rleo/TeleOCR-GGUFModel
- ldov/TeleOCRModel
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