End-to-end Document Recognition and Understanding with Dessurt
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Abstract (arXiv)
We introduce Dessurt, a relatively simple document understanding transformer capable of being fine-tuned on a greater variety of document tasks than prior methods. It receives a document image and task string as input and generates arbitrary text autoregressively as output. Because Dessurt is an end-to-end architecture that performs text recognition in addition to the document understanding, it does not require an external recognition model as prior methods do. Dessurt is a more flexible model than prior methods and is able to handle a variety of document domains and tasks. We show that this model is effective at 9 different dataset-task combinations.
Key facts. Cited by 73 papers in the map (data through 7 Oct 2026). Builds on 25 of its 40 references that are in the map. First posted on arXiv 30 Mar 2022.
Builds on
25 of 40 references.
References · 25
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- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
- 2015Distilling the Knowledge in a Neural Networkcited by 10,076
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- 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,288
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- 2021DocFormer: End-to-End Transformer for Document Understandingcited by 254
- 2015Evaluation of Deep Convolutional Nets for Document Image Classification and Retrievalcited by 212
13 more
- 2021Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformercited by 134
- 2021BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documentscited by 104
- 2020OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfoldcited by 53
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- 2020Text and Style Conditioned GAN for Generation of Offline Handwriting Linescited by 35
- 2019Deep Visual Template-Free Form Parsingcited by 24
- 2021Visual FUDGE: Form Understanding via Dynamic Graph Editingcited by 15
- 2021Cost-effective End-to-end Information Extraction for Semi-structured Document Imagescited by 14
- 2021Asking questions on handwritten document collectionscited by 14
- 2019A Computationally Efficient Pipeline Approach to Full Page Offline Handwritten Text Recognitioncited by 9
- 2021DocReader: Bounding-Box Free Training of a Document Information Extraction Modelcited by 4
- 2022Recognition-free Question Answering on Handwritten Document Collectionscited by 3
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Citing papers per year: 2022: 5; 2023: 20; 2024: 28; 2025: 13; 2026: 7.
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