Datasets › ICDAR 2013
ICDAR 2013
The ICDAR 2013 dataset consists of 229 training images and 233 testing images, with word-level annotations provided. It is the standard benchmark dataset for evaluating near-horizontal text detection.
Source: Single Shot Text Detector with Regional Attention Image Source: https://plos.figshare.com/articles/Detection_examples_of_the_proposed_method_on_the_ICDAR_2013_dataset_17_/5325856
Benchmarks archive 2025-07-28
All 3 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Scene Text Recognition | ICDAR2013 | CLIP4STR-L* Accuracy 99.42 | An Empirical Study of Scaling Law for OCR | large-ocr-model/large-ocr-model.github.io | 38 | Compare |
| Scene Text Detection | ICDAR 2013 | TextFuseNet (ResNeXt-101) F-Measure 94.61% | TextFuseNet: Scene Text Detection with Richer Fused Features | ying09/TextFuseNet +5 | 16 | Compare |
| Table Detection | ICDAR2013 | cascadetabnet Avg F1 1.0 | CascadeTabNet: An approach for end to end table... | DevashishPrasad/CascadeTabNet +2 | 3 | Compare |
Papers archive 2025-07-28
30 shown of 50 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 246. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
The full list of 50 is in the JSON twin.
Dataset loaders archive 2025-07-28
3 loaders as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Unknown
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- ICDAR 2013
- ICDAR2013
2 variant names, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections