Document Image Classification
24 papers with code • 8 benchmarks • 4 datasets
Document image classification is the task of classifying documents based on images of their contents.
( Image credit: Real-Time Document Image Classification using Deep CNN and Extreme Learning Machines )
Benchmarks
These leaderboards are used to track progress in Document Image Classification
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Libraries
Use these libraries to find Document Image Classification models and implementations
RVL-CDIP
Tobacco-3482
Most implemented papers
DocXClassifier: High Performance Explainable Deep Network for Document Image Classification
saifullah3396/docxclassifier
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TechArXiv 2022
Our approach achieves a new peak performance in image-based classification on two popular document datasets, namely RVL-CDIP and Tobacco3482, with a top-1 classification accuracy of 94. 17% and 95. 57% on the two datasets, respectively.
Multimodal Side-Tuning for Document Classification
thezingaro/multimodal-side-tuning
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In this paper, we propose to exploit the side-tuning framework for multimodal document classification.
StrucTexTv2: Masked Visual-Textual Prediction for Document Image Pre-training
Compared to the masked multi-modal modeling methods for document image understanding that rely on both the image and text modalities, StrucTexTv2 models image-only input and potentially deals with more application scenarios free from OCR pre-processing.
SUT: a new multi-purpose synthetic dataset for Farsi document image analysis
This paper introduces a new large-scale dataset for Farsi document images, named SUT, which aims to tackle the challenges associated with obtaining diverse and substantial ground-truth data for supervised models in document image analysis (DIA) tasks, such as document image classification, text detection and recognition, and information retrieval.
