Document AI: Benchmarks, Models and Applications
- URL: http://arxiv.org/abs/2111.08609v1
- Date: Tue, 16 Nov 2021 16:43:07 GMT
- Title: Document AI: Benchmarks, Models and Applications
- Authors: Lei Cui, Yiheng Xu, Tengchao Lv, Furu Wei
- Abstract summary: Document AI refers to the techniques for automatically reading, understanding, and analyzing business documents.
In recent years, the popularity of deep learning technology has greatly advanced the development of Document AI.
This paper briefly reviews some of the representative models, tasks, and benchmark datasets.
- Score: 35.46858492311289
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Document AI, or Document Intelligence, is a relatively new research topic
that refers to the techniques for automatically reading, understanding, and
analyzing business documents. It is an important research direction for natural
language processing and computer vision. In recent years, the popularity of
deep learning technology has greatly advanced the development of Document AI,
such as document layout analysis, visual information extraction, document
visual question answering, document image classification, etc. This paper
briefly reviews some of the representative models, tasks, and benchmark
datasets. Furthermore, we also introduce early-stage heuristic rule-based
document analysis, statistical machine learning algorithms, and deep learning
approaches especially pre-training methods. Finally, we look into future
directions for Document AI research.
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