Union14M: A Unified Benchmark for Scene Text Recognition.

Next-generation STR benchmark with 4M labeled + 10M unlabeled images. Accuracy drops 33-48% vs standard benchmarks (IIIT5K etc.), exposing real-world challenges like artistic text, multi-oriented, and occluded text.

Best published scores.

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

Primary

accuracy · higher is better

1 steps
of state of the art.

Each row below marks a model that broke the previous record on accuracy. Intermediate submissions are kept in the leaderboard above; only SOTA-setting entries are re-listed here.

Higher scores win. Each subsequent entry improved upon the previous best.

1. Mar 27, 2026CLIP4STR-BResearch70.80

Neighbouring benchmarks.

Other Scene Text Detection datasets on Codesota.

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.

• 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