SOTAVerified

Document Image Classification

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 )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 50 papers

TitleStatusHype
Zero-Shot Prompting and Few-Shot Fine-Tuning: Revisiting Document Image Classification Using Large Language Models—0
DoPTA: Improving Document Layout Analysis using Patch-Text Alignment—0
DocXplain: A Novel Model-Agnostic Explainability Method for Document Image Classification—0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications—0
Multimodal Adaptive Inference for Document Image Classification with Anytime Early ExitingCode0
CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification—0
LayoutLLM: Large Language Model Instruction Tuning for Visually Rich Document Understanding—0
Automatic Recognition of Learning Resource Category in a Digital LibraryCode0
SUT: a new multi-purpose synthetic dataset for Farsi document image analysisCode0
A Multi-Modal Multilingual Benchmark for Document Image Classification—0
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All datasetsRVL-CDIPTobacco-3482Noisy Bangla CharactersNoisy Bangla NumeralAIPN-MNISTNoisy MNISTSUT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EAMLAccuracy97.7—Unverified
2Cross-ModalAccuracy97.05—Unverified
3DocFormerBASEAccuracy96.17—Unverified
4LayoutLMV3LargeAccuracy95.93—Unverified
5LiLT[EN-R]BASEAccuracy95.68—Unverified
6LayoutLMv2LARGEAccuracy95.64—Unverified
7TILT-LargeAccuracy95.52—Unverified
8DocFormer largeAccuracy95.5—Unverified
9LayoutLMv3BASEAccuracy95.44—Unverified
10DonutAccuracy95.3—Unverified