# A Survey of Deep Learning Approaches for OCR and Document Understanding

arXiv: https://arxiv.org/abs/2011.13534 · HTML: https://mlsanity.com/paper/2011.13534/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Nov 2020.

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

- [Towards Complex Document Understanding By Discrete Reasoning](https://mlsanity.com/paper/2207.11871/) (2022)
- [Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction](https://mlsanity.com/paper/2410.21169/) (2024)
- [Deep Learning based Visually Rich Document Content Understanding: A Survey](https://mlsanity.com/paper/2408.01287/) (2024)
- [Towards Visual Text Grounding of Multimodal Large Language Model](https://mlsanity.com/paper/2504.04974/) (2025)
- [Multimodal Large Language Models for Text-rich Image Understanding: A Comprehensive Review](https://mlsanity.com/paper/2502.16586/) (2025)
- [Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding](https://mlsanity.com/paper/2510.15253/) (2025)
- [Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval](https://mlsanity.com/paper/2602.19961/) (2026)
- [Transformers and Language Models in Form Understanding: A Comprehensive Review of Scanned Document Analysis](https://mlsanity.com/paper/2403.04080/) (2024)
- [Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review](https://mlsanity.com/paper/2408.06345/) (2024)
- [Detection Masking for Improved OCR on Noisy Documents](https://mlsanity.com/paper/2205.08257/) (2022)
- [Literature Review: Computer Vision Applications in Transportation Logistics and Warehousing](https://mlsanity.com/paper/2304.06009/) (2023)
- [Handwritten and Printed Text Segmentation: A Signature Case Study](https://mlsanity.com/paper/2307.07887/) (2023)
- [DeepCPCFG: Deep Learning and Context Free Grammars for End-to-End Information Extraction](https://mlsanity.com/paper/2103.05908/) (2021)
- [Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts](https://mlsanity.com/paper/2304.03427/) (2023)
- [DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models](https://mlsanity.com/paper/2410.03061/) (2024)
- [Revise: A Framework for Revising OCRed text in Practical Information Systems with Data Contamination Strategy](https://mlsanity.com/paper/2604.08115/) (2026)
- [TransDocAnalyser: A Framework for Offline Semi-structured Handwritten Document Analysis in the Legal Domain](https://mlsanity.com/paper/2306.02142/) (2023)
- [Image-to-LaTeX Converter for Mathematical Formulas and Text](https://mlsanity.com/paper/2408.04015/) (2024)
- [Confidence-Aware Document OCR Error Detection](https://mlsanity.com/paper/2409.04117/) (2024)
- [Leveraging Distillation Techniques for Document Understanding: A Case Study with FLAN-T5](https://mlsanity.com/paper/2409.11282/) (2024)
- [PerSRV: Personalized Sticker Retrieval with Vision-Language Model](https://mlsanity.com/paper/2410.21801/) (2024)
- [Multi-Modal Vision vs. Text-Based Parsing: Benchmarking LLM Strategies for Invoice Processing](https://mlsanity.com/paper/2509.04469/) (2025)
- [DocReward: A Document Reward Model for Structuring and Stylizing](https://mlsanity.com/paper/2510.11391/) (2025)
- [Robustness of Structured Data Extraction from Perspectively Distorted Documents](https://mlsanity.com/paper/2511.17607/) (2025)
- [Q-Mask: Query-driven Causal Masks for Text Anchoring in OCR-Oriented Vision-Language Models](https://mlsanity.com/paper/2604.00161/) (2026)
- [Amnesia by Design, Memory By Necessity: Persistent State for Document Intelligence](https://mlsanity.com/paper/2609.32041/) (2026)
- [VORTEX: A Spatial Computing Framework for Optimized Drone Telemetry Extraction from First-Person View Flight Data](https://mlsanity.com/paper/2412.18505/) (2024)
- [A document is worth a structured record: Principled inductive bias design for document recognition](https://mlsanity.com/paper/2507.08458/) (2025)
- [Finding Needles in Images: Can Multimodal LLMs Locate Fine Details?](https://mlsanity.com/paper/2508.05053/) (2025)
- [Structured Data Extraction from Real Estate Documents using Clustering, Classification, and Large Language Models](https://mlsanity.com/paper/2607.06012/) (2026)

## Abstract (arXiv)

Documents are a core part of many businesses in many fields such as law, finance, and technology among others. Automatic understanding of documents such as invoices, contracts, and resumes is lucrative, opening up many new avenues of business. The fields of natural language processing and computer vision have seen tremendous progress through the development of deep learning such that these methods have started to become infused in contemporary document understanding systems. In this survey paper, we review different techniques for document understanding for documents written in English and consolidate methodologies present in literature to act as a jumping-off point for researchers exploring this area.