English

Modular Multimodal Architecture for Document Classification

Computer Vision and Pattern Recognition 2019-12-11 v1

Abstract

Page classification is a crucial component to any document analysis system, allowing for complex branching control flows for different components of a given document. Utilizing both the visual and textual content of a page, the proposed method exceeds the current state-of-the-art performance on the RVL-CDIP benchmark at 93.03% test accuracy.

Keywords

Cite

@article{arxiv.1912.04376,
  title  = {Modular Multimodal Architecture for Document Classification},
  author = {Tyler Dauphinee and Nikunj Patel and Mohammad Rashidi},
  journal= {arXiv preprint arXiv:1912.04376},
  year   = {2019}
}
R2 v1 2026-06-23T12:40:42.509Z