Papers › SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and...

SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition

19 Mar 2022CVPR 2022 1arXiv:2203.10209archive 2025-07-28

Mingxin Huang, Yuliang Liu, Zhenghao Peng, Chongyu Liu, Dahua Lin, Shenggao Zhu, Nicholas Yuan, Kai Ding, Lianwen Jin

End-to-end scene text spotting has attracted great attention in recent years due to the success of excavating the intrinsic synergy of the scene text detection and recognition. However, recent state-of-the-art methods usually incorporate detection and recognition simply by sharing the backbone, which does not directly take advantage of the feature interaction between the two tasks. In this paper, we propose a new end-to-end scene text spotting framework termed SwinTextSpotter. Using a transformer encoder with dynamic head as the detector, we unify the two tasks with a novel Recognition Conversion mechanism to explicitly guide text localization through recognition loss. The straightforward design results in a concise framework that requires neither additional rectification module nor character-level annotation for the arbitrarily-shaped text. Qualitative and quantitative experiments on multi-oriented datasets RoIC13 and ICDAR 2015, arbitrarily-shaped datasets Total-Text and CTW1500, and multi-lingual datasets ReCTS (Chinese) and VinText (Vietnamese) demonstrate SwinTextSpotter significantly outperforms existing methods. Code is available at https://github.com/mxin262/SwinTextSpotter.

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mxin262/swintextspotter officialmentioned in papermentioned on GitHubpytorch report
jacobtyo/swintextspotter mentioned on GitHubpytorch report

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Tasks

Scene Text DetectionText DetectionText Spotting

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Text Spotting ICDAR 2015 SwinTextSpotter F-measure (%) - Generic Lexicon 70.5 #9 of 18 Archive leaderboard report
Text Spotting ICDAR 2015 SwinTextSpotter F-measure (%) - Strong Lexicon 83.9 #9 of 18 Archive leaderboard report
Text Spotting ICDAR 2015 SwinTextSpotter F-measure (%) - Weak Lexicon 77.3 #9 of 18 Archive leaderboard report
Text Spotting Inverse-Text SwinTextSpotter F-measure (%) - Full Lexicon 67.9 #3 of 9 Archive leaderboard report
Text Spotting Inverse-Text SwinTextSpotter F-measure (%) - No Lexicon 55.4 #3 of 9 Archive leaderboard report
Text Spotting SCUT-CTW1500 SwinTextSpotter F-Measure (%) - Full Lexicon 77.0 #10 of 11 Archive leaderboard report
Text Spotting SCUT-CTW1500 SwinTextSpotter F-measure (%) - No Lexicon 51.8 #10 of 11 Archive leaderboard report
Text Spotting Total-Text SwinTextSpotter F-measure (%) - Full Lexicon 84.1 #8 of 12 Archive leaderboard report
Text Spotting Total-Text SwinTextSpotter F-measure (%) - No Lexicon 74.3 #8 of 12 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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