Papers › Total-Text: A Comprehensive Dataset for Scene Text Detection and Recognition

Total-Text: A Comprehensive Dataset for Scene Text Detection and Recognition

28 Oct 2017arXiv:1710.10400archive 2025-07-28

Chee Kheng Chng, Chee Seng Chan

Text in curve orientation, despite being one of the common text orientations in real world environment, has close to zero existence in well received scene text datasets such as ICDAR2013 and MSRA-TD500. The main motivation of Total-Text is to fill this gap and facilitate a new research direction for the scene text community. On top of the conventional horizontal and multi-oriented texts, it features curved-oriented text. Total-Text is highly diversified in orientations, more than half of its images have a combination of more than two orientations. Recently, a new breed of solutions that casted text detection as a segmentation problem has demonstrated their effectiveness against multi-oriented text. In order to evaluate its robustness against curved text, we fine-tuned DeconvNet and benchmark it on Total-Text. Total-Text with its annotation is available at https://github.com/cs-chan/Total-Text-Dataset

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cs-chan/Total-Text-Dataset officialmentioned in papermentioned on GitHubBSD-3-Clause report

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Curved Text DetectionScene Text DetectionScene Text RecognitionText Detection

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Total-Text

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Scene Text Detection Total-Text Ch,ng et al. F-Measure 36.0% #27 of 27 Archive leaderboard report
Scene Text Detection Total-Text Ch,ng et al. Precision 40.0 #27 of 27 Archive leaderboard report
Scene Text Detection Total-Text Ch,ng et al. Recall 33.0 #27 of 27 Archive leaderboard report

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