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Dataset from Papers With Code

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§ 01 · Leaderboard

Best published scores.

3 results indexed across 1 metric. Shaded row marks current SOTA; ties broken by submission date.

Primary: accuracy · higher is better

1-1-accuracy

3 rows

#	Model	Org	Submitted	Paper / code	1-1-accuracy
01	CLIP4STR-L	—	May 2023	CLIP4STR: A Simple Baseline for Scene Text Recognition w… · code	82.70
02	CLIP4STR-B	Research	May 2023	CLIP4STR: A Simple Baseline for Scene Text Recognition w… · code	79.80
03	CCD-ViT-Base	—	Nov 2022	Self-supervised Character-to-Character Distillation for … · code	77.30

Fig 2 · Rows sorted by score within each metric. Shaded row marks SOTA. Dates reflect model or paper release where available, otherwise the date Codesota accessed the source.

§ 04 · Literature

2 papers
tied to this benchmark.

Every paper below corresponds to at least one row in the leaderboard above. Click through for the arXiv preprint and, when available, the reference implementation.

CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
May 2023·CLIP4STR-L, CLIP4STR-B
arXiv ↗Code
Self-supervised Character-to-Character Distillation for Text Recognition
Nov 2022·CCD-ViT-Base
arXiv ↗Code

§ 06 · Contribute

Have a score that beats
this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

Submit a result ↵Read submission guide

What a submission needs

01A public checkpoint or API endpoint
02A reproduction script with frozen commit + seed
03Declared evaluation environment (Python, deps)
04One row per metric declared by this dataset
05A contact so we can follow up on discrepancies

host.

Best published scores.

2 paperstied to this benchmark.

Neighbouring benchmarks.

Have a score that beatsthis table?

2 papers
tied to this benchmark.

Have a score that beats
this table?