Codesota · Benchmark · icdar2013Home/Leaderboards/Vision & Documents/Document OCR/icdar2013
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icdar2013.

icdar2013 is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for icdar2013.

Paper ↗Leaderboard ↓
§ 01 · SOTA history

Year over year.

§ 02 · Leaderboard

Results by metric.

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Accuracy

Accuracy is the reported evaluation metric for icdar2013. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Accuracyverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01DTrOCR 105M
From paper: DTrOCR: Decoder-only Transformer for Optical Character Recognition
verified99.42023Paper ↗Code ↗Looks wrong?
02CLIP4STR-L (DataComp-1B)
From paper: CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
verified992023Paper ↗Code ↗Looks wrong?
03CLIP4STR-L
From paper: An Empirical Study of Scaling Law for OCR
verified98.52023Paper ↗Code ↗Source ↗Looks wrong?
04MGP-STR
From paper: Multi-Granularity Prediction for Scene Text Recognition
verified98.52022Paper ↗Code ↗Looks wrong?
05CLIP4STR-B
From paper: CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
verified98.32023Paper ↗Code ↗Looks wrong?
06CCD-ViT-Small(ARD_2.8M)
From paper: Self-supervised Character-to-Character Distillation for Text Recognition
verified98.32022Paper ↗Code ↗Looks wrong?
07CCD-ViT-Base(ARD_2.8M)
From paper: Self-supervised Character-to-Character Distillation for Text Recognition
verified98.32022Paper ↗Code ↗Looks wrong?
08MATRN
From paper: Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features
verified97.92021Paper ↗Code ↗Looks wrong?
09SIGA_T
From paper: Self-supervised Implicit Glyph Attention for Text Recognition
verified97.82022Paper ↗Code ↗Looks wrong?
10S-GTR
From paper: Visual Semantics Allow for Textual Reasoning Better in Scene Text Recognition
verified97.82021Paper ↗Code ↗Looks wrong?
11DPAN
From paper: Look Back Again: Dual Parallel Attention Network for Accurate and Robust Scene Text Recognition
verified97.72021Paper ↗Code ↗Looks wrong?
12CDistNet (Ours)
From paper: CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition
verified97.672021Paper ↗Code ↗Looks wrong?
13CCD-ViT-Tiny(ARD_2.8M)
From paper: Self-supervised Character-to-Character Distillation for Text Recognition
verified97.52022Paper ↗Code ↗Looks wrong?
14SVTR-L (Large)
From paper: SVTR: Scene Text Recognition with a Single Visual Model
verified97.22022Paper ↗Code ↗Looks wrong?
15SVTR-B (Base)
From paper: SVTR: Scene Text Recognition with a Single Visual Model
verified97.12022Paper ↗Code ↗Looks wrong?
16DiffusionSTR
From paper: DiffusionSTR: Diffusion Model for Scene Text Recognition
verified97.12023Paper ↗Looks wrong?
17Yet Another Text Recognizer
From paper: Why You Should Try the Real Data for the Scene Text Recognition
verified96.82021Paper ↗Code ↗Looks wrong?
18SVTR-T (Tiny)
From paper: SVTR: Scene Text Recognition with a Single Visual Model
verified96.32022Paper ↗Code ↗Looks wrong?
19SVTR-S (Small)
From paper: SVTR: Scene Text Recognition with a Single Visual Model
verified95.72022Paper ↗Code ↗Looks wrong?
20SRN
From paper: Towards Accurate Scene Text Recognition with Semantic Reasoning Networks
verified95.52020Paper ↗Code ↗Looks wrong?
21RCEED
From paper: Representation and Correlation Enhanced Encoder-Decoder Framework for Scene Text Recognition
verified94.72021Paper ↗Code ↗Looks wrong?
22SATRN
From paper: On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention
verified94.12019Paper ↗Code ↗Looks wrong?
23DAN
From paper: Decoupled Attention Network for Text Recognition
verified93.92019Paper ↗Code ↗Looks wrong?
24CSTR
From paper: Revisiting Classification Perspective on Scene Text Recognition
verified93.22021Paper ↗Code ↗Looks wrong?
25TextScanner
From paper: TextScanner: Reading Characters in Order for Robust Scene Text Recognition
verified92.92019Paper ↗Looks wrong?
26SAFL
From paper: SAFL: A Self-Attention Scene Text Recognizer with Focal Loss
verified92.82022Paper ↗Code ↗Looks wrong?
27SEED
From paper: SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition
verified92.82020Paper ↗Code ↗Looks wrong?
28ViTSTR
From paper: Vision Transformer for Fast and Efficient Scene Text Recognition
verified92.42021Paper ↗Code ↗Looks wrong?
29Baek et al.
From paper: What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
verified92.32019Paper ↗Code ↗Looks wrong?
30ASTER
From paper: ASTER: An Attentional Scene Text Recognizer with Flexible Rectification
verified91.82018Paper ↗Code ↗Looks wrong?
31CA-FCN
From paper: Scene Text Recognition from Two-Dimensional Perspective
verified91.52018Paper ↗Looks wrong?
32SAR
From paper: Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
verified912018Paper ↗Code ↗Looks wrong?
33STAR-Net
From paper: Star-net: A spatial attention residue network for scene text recognition.
verified89.12016Paper ↗Code ↗Looks wrong?
34RARE
From paper: Robust Scene Text Recognition with Automatic Rectification
verified88.62016Paper ↗Code ↗Looks wrong?
35CRNN
From paper: An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
verified86.72015Paper ↗Code ↗Looks wrong?
36CHAR
From paper: Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
verified79.52014Paper ↗Code ↗Looks wrong?

Avg F1

Avg F1 is the reported evaluation metric for icdar2013. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Avg F1verifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01CDeCNet
From paper: CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
verified1.002020Paper ↗Code ↗Looks wrong?
02cascadetabnet
From paper: CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents
verified1.002020Paper ↗Code ↗Looks wrong?
03TableNet
From paper: TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images
verified0.972020Paper ↗Code ↗Looks wrong?
§ 04 · Submit a result

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