Codesota · Benchmark · read-2016Home/Leaderboards/Vision & Documents/Document OCR/read-2016
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read-2016.

read-2016 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 read-2016.

Paper Leaderboard
§ 01 · SOTA history

Year over year.

§ 02 · Leaderboard

Results by metric.

Only 2 models on this benchmark
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Wer

Wer is the reported evaluation metric for read-2016. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Lower is better

Trust tiers for Werverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01DAN
From paper: DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition
verified13.632022Paper ↗Code ↗Looks wrong?
02HTR-VT(line-level)
From paper: HTR-VT: Handwritten Text Recognition with Vision Transformer
verified16.52024Paper ↗Code ↗Looks wrong?

Cer

Cer is the reported evaluation metric for read-2016. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Lower is better

Trust tiers for Cerverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01DAN
From paper: DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition
verified3.222022Paper ↗Code ↗Looks wrong?
02HTR-VT(line-level)
From paper: HTR-VT: Handwritten Text Recognition with Vision Transformer
verified3.902024Paper ↗Code ↗Looks wrong?
§ 04 · Submit a result

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