Document Image Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

8 leaderboard tables shown for this task, 8 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 25 papers with code (50 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• RoBERTa: A Robustly Optimized BERT Pretraining Approach
  26 Jul 2019 67 repositories listed Syntology ran 22 of 48 samples · 26 unverified · 23 pointer-only (licence)
  Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging.
• Training data-efficient image transformers & distillation through attention
  23 Dec 2020 40 repositories listed Syntology ran 12 of 19 samples · 7 unverified · 3 pointer-only (licence)
  In this work, we produce a competitive convolution-free transformer by training on Imagenet only.
• LayoutLM: Pre-training of Text and Layout for Document Image Understanding
  31 Dec 2019 19 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 1 pointer-only (licence)
  In this paper, we propose the \textbf{LayoutLM} to jointly model interactions between text and layout information across scanned document images, which is beneficial for a great number of real-world document image…
• LayoutLM: Pre-training of Text and Layout for Document Image Understanding
  31 Dec 2019 19 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 1 pointer-only (licence)
  In this paper, we propose the \textbf{LayoutLM} to jointly model interactions between text and layout information across scanned document images, which is beneficial for a great number of real-world document image…
• BEiT: BERT Pre-Training of Image Transformers
  15 Jun 2021 14 repositories listed Syntology ran 6 of 11 samples · 5 unverified
  We first "tokenize" the original image into visual tokens.
• LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding
  29 Dec 2020 9 repositories listed
  Pre-training of text and layout has proved effective in a variety of visually-rich document understanding tasks due to its effective model architecture and the advantage of large-scale unlabeled scanned/digital-born…
• LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understanding
  18 Apr 2021 6 repositories listed
  In this paper, we present LayoutXLM, a multimodal pre-trained model for multilingual document understanding, which aims to bridge the language barriers for visually-rich document understanding.
• LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding
  28 Feb 2022 5 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  LiLT can be pre-trained on the structured documents of a single language and then directly fine-tuned on other languages with the corresponding off-the-shelf monolingual/multilingual pre-trained textual models.
• OCR-free Document Understanding Transformer
  30 Nov 2021 5 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  Current Visual Document Understanding (VDU) methods outsource the task of reading text to off-the-shelf Optical Character Recognition (OCR) engines and focus on the understanding task with the OCR outputs.
• Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification
  11 Apr 2017 5 repositories listed
  We present an exhaustive investigation of recent Deep Learning architectures, algorithms, and strategies for the task of document image classification to finally reduce the error by more than half.
• Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification
  11 Apr 2017 5 repositories listed
  We present an exhaustive investigation of recent Deep Learning architectures, algorithms, and strategies for the task of document image classification to finally reduce the error by more than half.
• LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking
  18 Apr 2022 4 repositories listed
  In this paper, we propose \textbf{LayoutLMv3} to pre-train multimodal Transformers for Document AI with unified text and image masking.
• LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking
  18 Apr 2022 4 repositories listed
  In this paper, we propose \textbf{LayoutLMv3} to pre-train multimodal Transformers for Document AI with unified text and image masking.
• DiT: Self-supervised Pre-training for Document Image Transformer
  4 Mar 2022 4 repositories listed Syntology ran 0 of 11 samples · 11 unverified
  We leverage DiT as the backbone network in a variety of vision-based Document AI tasks, including document image classification, document layout analysis, table detection as well as text detection for OCR.
• DiT: Self-supervised Pre-training for Document Image Transformer
  4 Mar 2022 4 repositories listed Syntology ran 0 of 11 samples · 11 unverified
  We leverage DiT as the backbone network in a variety of vision-based Document AI tasks, including document image classification, document layout analysis, table detection as well as text detection for OCR.
• Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks
  29 Jan 2018 4 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  In this work, a region-based Deep Convolutional Neural Network framework is proposed for document structure learning.
• Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks
  29 Jan 2018 4 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  In this work, a region-based Deep Convolutional Neural Network framework is proposed for document structure learning.
• Revisiting ResNets: Improved Training and Scaling Strategies
  13 Mar 2021 3 repositories listed
  Using improved training and scaling strategies, we design a family of ResNet architectures, ResNet-RS, which are 1.
• Automatic Recognition of Learning Resource Category in a Digital Library
  28 Nov 2023 2 repositories listed
  Digital libraries often face the challenge of processing a large volume of diverse document types.
• Automatic Recognition of Learning Resource Category in a Digital Library
  28 Nov 2023 2 repositories listed
  Digital libraries often face the challenge of processing a large volume of diverse document types.
• ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding
  12 Oct 2022 2 repositories listed Syntology ran 2 of 7 samples · 5 unverified
  Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding.
• ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding
  12 Oct 2022 2 repositories listed Syntology ran 2 of 7 samples · 5 unverified
  Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding.
• Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting
  21 May 2024 1 repository listed
  Our multimodal EE design preserves the model's predictive capabilities, enhancing both speed and latency.
• Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting
  21 May 2024 1 repository listed
  Our multimodal EE design preserves the model's predictive capabilities, enhancing both speed and latency.
• SUT: a new multi-purpose synthetic dataset for Farsi document image analysis
  27 Nov 2023 1 repository listed
  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…
• SUT: a new multi-purpose synthetic dataset for Farsi document image analysis
  27 Nov 2023 1 repository listed
  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…
• StrucTexTv2: Masked Visual-Textual Prediction for Document Image Pre-training
  1 Mar 2023 1 repository listed
  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…
• Multimodal Side-Tuning for Document Classification
  16 Jan 2023 1 repository listed
  In this paper, we propose to exploit the side-tuning framework for multimodal document classification.
• DocXClassifier: High Performance Explainable Deep Network for Document Image Classification
  17 Mar 2022 1 repository listed
  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.
• DocXClassifier: High Performance Explainable Deep Network for Document Image Classification
  17 Mar 2022 1 repository listed
  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.

Syntology lines on 13 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.