# dhSegment: A generic deep-learning approach for document segmentation

arXiv: https://arxiv.org/abs/1804.10371 · HTML: https://mlsanity.com/paper/1804.10371/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2018.

## Built on by (most cited first, 30 of 32)

- [Document AI: Benchmarks, Models and Applications](https://mlsanity.com/paper/2111.08609/) (2021)
- [DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition](https://mlsanity.com/paper/2203.12273/) (2022)
- [LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis](https://mlsanity.com/paper/2103.15348/) (2021)
- [M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout Analysis](https://mlsanity.com/paper/2305.08719/) (2023)
- [A Survey of Historical Document Image Datasets](https://mlsanity.com/paper/2203.08504/) (2022)
- [SPAN: a Simple Predict & Align Network for Handwritten Paragraph Recognition](https://mlsanity.com/paper/2102.08742/) (2021)
- [DocSegTr: An Instance-Level End-to-End Document Image Segmentation Transformer](https://mlsanity.com/paper/2201.11438/) (2022)
- [SwinDocSegmenter: An End-to-End Unified Domain Adaptive Transformer for Document Instance Segmentation](https://mlsanity.com/paper/2305.04609/) (2023)
- [Faster DAN: Multi-target Queries with Document Positional Encoding for End-to-end Handwritten Document Recognition](https://mlsanity.com/paper/2301.10593/) (2023)
- [End-to-End Hierarchical Relation Extraction for Generic Form Understanding](https://mlsanity.com/paper/2106.00980/) (2021)
- [DocBed: A Multi-Stage OCR Solution for Documents with Complex Layouts](https://mlsanity.com/paper/2202.01414/) (2022)
- [Document Intelligence in the Era of Large Language Models: A Survey](https://mlsanity.com/paper/2510.13366/) (2025)
- [End-to-End Information Extraction by Character-Level Embedding and Multi-Stage Attentional U-Net](https://mlsanity.com/paper/2106.00952/) (2021)
- [Robust Text Line Detection in Historical Documents: Learning and Evaluation Methods](https://mlsanity.com/paper/2203.12346/) (2022)
- [Large Scale Genealogical Information Extraction From Handwritten Quebec Parish Records](https://mlsanity.com/paper/2304.14044/) (2023)
- [The Socface Project: Large-Scale Collection, Processing, and Analysis of a Century of French Censuses](https://mlsanity.com/paper/2404.18706/) (2024)
- [Efficient few-shot learning for pixel-precise handwritten document layout analysis](https://mlsanity.com/paper/2210.15570/) (2022)
- [Normalized vs Diplomatic Annotation: A Case Study of Automatic Information Extraction from Handwritten Uruguayan Birth Certificates](https://mlsanity.com/paper/2507.08636/) (2025)
- [Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data](https://mlsanity.com/paper/2107.06777/) (2021)
- [Palmira: A Deep Deformable Network for Instance Segmentation of Dense and Uneven Layouts in Handwritten Manuscripts](https://mlsanity.com/paper/2108.09436/) (2021)
- [GraphKD: Exploring Knowledge Distillation Towards Document Object Detection with Structured Graph Creation](https://mlsanity.com/paper/2402.11401/) (2024)
- [PILOT: A Promptable Interleaved Layout-aware OCR Transformer](https://mlsanity.com/paper/2504.03621/) (2025)
- [Text line extraction using fully convolutional network and energy minimization](https://mlsanity.com/paper/2101.07370/) (2021)
- [Evaluation of a Region Proposal Architecture for Multi-task Document Layout Analysis](https://mlsanity.com/paper/2106.11797/) (2021)
- [Including Keyword Position in Image-based Models for Act Segmentation of Historical Registers](https://mlsanity.com/paper/2109.08477/) (2021)
- [Entry Separation using a Mixed Visual and Textual Language Model: Application to 19th century French Trade Directories](https://mlsanity.com/paper/2302.08948/) (2023)
- [An extensible point-based method for data chart value detection](https://mlsanity.com/paper/2308.11788/) (2023)
- [OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis](https://mlsanity.com/paper/2110.02069/) (2021)
- [Cross-codex Learning for Reliable Scribe Identification in Medieval Manuscripts](https://mlsanity.com/paper/2312.04296/) (2023)
- [End-to-End Text Line Detection and Ordering](https://mlsanity.com/paper/2606.04166/) (2026)

## Abstract (arXiv)

In recent years there have been multiple successful attempts tackling document processing problems separately by designing task specific hand-tuned strategies. We argue that the diversity of historical document processing tasks prohibits to solve them one at a time and shows a need for designing generic approaches in order to handle the variability of historical series. In this paper, we address multiple tasks simultaneously such as page extraction, baseline extraction, layout analysis or multiple typologies of illustrations and photograph extraction. We propose an open-source implementation of a CNN-based pixel-wise predictor coupled with task dependent post-processing blocks. We show that a single CNN-architecture can be used across tasks with competitive results. Moreover most of the task-specific post-precessing steps can be decomposed in a small number of simple and standard reusable operations, adding to the flexibility of our approach.