# DocEnTr: An End-to-End Document Image Enhancement Transformer

arXiv: https://arxiv.org/abs/2201.10252 · HTML: https://mlsanity.com/paper/2201.10252/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 44 references that are in the map.
- First posted on arXiv 25 Jan 2022.

## Builds on (most cited first, 20 of 20)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [SwinIR: Image Restoration Using Swin Transformer](https://mlsanity.com/paper/2108.10257/) (2021)
- [LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding](https://mlsanity.com/paper/2012.14740/) (2020)
- [DocFormer: End-to-End Transformer for Document Understanding](https://mlsanity.com/paper/2106.11539/) (2021)
- [LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement](https://mlsanity.com/paper/1511.03995/) (2015)
- [SelfDoc: Self-Supervised Document Representation Learning](https://mlsanity.com/paper/2106.03331/) (2021)
- [LaTr: Layout-Aware Transformer for Scene-Text VQA](https://mlsanity.com/paper/2112.12494/) (2021)
- [DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement](https://mlsanity.com/paper/2010.08764/) (2020)
- [DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction](https://mlsanity.com/paper/2110.12942/) (2021)
- [Document Image Binarization with Fully Convolutional Neural Networks](https://mlsanity.com/paper/1708.03276/) (2017)
- [A selectional auto-encoder approach for document image binarization](https://mlsanity.com/paper/1706.10241/) (2017)
- [Transformer-Based Approach for Joint Handwriting and Named Entity Recognition in Historical documents](https://mlsanity.com/paper/2112.04189/) (2021)
- [Improving Document Binarization via Adversarial Noise-Texture Augmentation](https://mlsanity.com/paper/1810.11120/) (2018)
- [Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement](https://mlsanity.com/paper/2105.12710/) (2021)
- [Patch redundancy in images: a statistical testing framework and some applications](https://mlsanity.com/paper/1904.06428/) (2019)

## Built on by (most cited first, 28 of 28)

- [DocDiff: Document Enhancement via Residual Diffusion Models](https://mlsanity.com/paper/2305.03892/) (2023)
- [OCR-IDL: OCR Annotations for Industry Document Library Dataset](https://mlsanity.com/paper/2202.12985/) (2022)
- [Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement](https://mlsanity.com/paper/2203.04814/) (2022)
- [High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer](https://mlsanity.com/paper/2410.22922/) (2024)
- [NAF-DPM: A Nonlinear Activation-Free Diffusion Probabilistic Model for Document Enhancement](https://mlsanity.com/paper/2404.05669/) (2024)
- [Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks](https://mlsanity.com/paper/2211.16098/) (2022)
- [DocBinFormer: A Two-Level Transformer Network for Effective Document Image Binarization](https://mlsanity.com/paper/2312.03568/) (2023)
- [ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents](https://mlsanity.com/paper/2303.03127/) (2023)
- [DocStormer: Revitalizing Multi-Degraded Colored Document Images to Pristine PDF](https://mlsanity.com/paper/2310.17910/) (2023)
- [Binarizing Documents by Leveraging both Space and Frequency](https://mlsanity.com/paper/2404.17243/) (2024)
- [A Layer-Wise Tokens-to-Token Transformer Network for Improved Historical Document Image Enhancement](https://mlsanity.com/paper/2312.03946/) (2023)
- [Unveiling Advanced Frequency Disentanglement Paradigm for Low-Light Image Enhancement](https://mlsanity.com/paper/2409.01641/) (2024)
- [TextDoctor: Unified Document Image Inpainting via Patch Pyramid Diffusion Models](https://mlsanity.com/paper/2503.04021/) (2025)
- [MFE-GAN: Efficient GAN-based Framework for Document Image Enhancement and Binarization with Multi-scale Feature Extraction](https://mlsanity.com/paper/2512.14114/) (2025)
- [Digitizing Historical Balance Sheet Data: A Practitioner's Guide](https://mlsanity.com/paper/2204.00052/) (2022)
- [Mutual Guidance and Residual Integration for Image Enhancement](https://mlsanity.com/paper/2211.13919/) (2022)
- [arXiVeri: Automatic table verification with GPT](https://mlsanity.com/paper/2306.07968/) (2023)
- [Semantic Segmentation Using Super Resolution Technique as Pre-Processing](https://mlsanity.com/paper/2306.15218/) (2023)
- [DECDM: Document Enhancement using Cycle-Consistent Diffusion Models](https://mlsanity.com/paper/2311.09625/) (2023)
- [LayeredDoc: Domain Adaptive Document Restoration with a Layer Separation Approach](https://mlsanity.com/paper/2406.08610/) (2024)
- [Unveiling Text in Challenging Stone Inscriptions: A Character-Context-Aware Patching Strategy for Binarization](https://mlsanity.com/paper/2601.03609/) (2026)
- [DeepMine-Mamba: Mitigating Information Dilution in Mamba-Based State Space Models for Document Image Binarization](https://mlsanity.com/paper/2606.08781/) (2026)
- [Variational Augmentation for Enhancing Historical Document Image Binarization](https://mlsanity.com/paper/2211.06581/) (2022)
- [MatteViT: High-Frequency-Aware Document Shadow Removal with Shadow Matte Guidance](https://mlsanity.com/paper/2512.08789/) (2025)
- [DocRevive: A Unified Pipeline for Document Text Restoration](https://mlsanity.com/paper/2604.10077/) (2026)
- [DR-Mamba: Automatic Inference-Time Domain Adaptation for Document Image Binarization via Sample-Conditioned Detail-Background Suppression](https://mlsanity.com/paper/2606.22625/) (2026)
- [SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation](https://mlsanity.com/paper/2607.06949/) (2026)
- [ENet-GP: Unified Document Image Restoration](https://mlsanity.com/paper/2609.33758/) (2026)

## Abstract (arXiv)

Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for proper usage. To address this challenge, we present a new encoder-decoder architecture based on vision transformers to enhance both machine-printed and handwritten document images, in an end-to-end fashion. The encoder operates directly on the pixel patches with their positional information without the use of any convolutional layers, while the decoder reconstructs a clean image from the encoded patches. Conducted experiments show a superiority of the proposed model compared to the state-of the-art methods on several DIBCO benchmarks. Code and models will be publicly available at: urlhttps://github.com/dali92002/DocEnTR.