The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Multi-oriented Scene Text Detection via Corner Localization and Region Segmentation
Open accessAbstract
Previous deep learning based state-of-the-art scene text detection methods can be roughly classified into two categories. The first category treats scene text as a type of general objects and follows general object detection paradigm to localize scene text by regressing the text box locations, but troubled by the arbitrary-orientation and large aspect ratios of scene text. The second one segments text regions directly, but mostly needs complex post processing. In this paper, we present a method that combines the ideas of the two types of methods while avoiding their shortcomings. We propose to detect scene text by localizing corner points of text bounding boxes and segmenting text regions in relative positions. In inference stage, candidate boxes are generated by sampling and grouping corner points, which are further scored by segmentation maps and suppressed by NMS. Compared with previous methods, our method can handle long oriented text naturally and doesn't need complex post processing. The experiments on ICDAR2013, ICDAR2015, MSRA-TD500, MLT and COCO-Text demonstrate that the proposed algorithm achieves better or comparable results in both accuracy and efficiency. Based on VGG16, it achieves an F-measure of 84.3% on ICDAR2015 and 81.5% on MSRA-TD500.
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Cites
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Microsoft COCO: Common Objects in Context
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Cited by
Gliding Vertex on the Horizontal Bounding Box for Multi-Oriented Object Detection
Xu, Y., Fu, M., Wang, Q., Wang, Y., Chen, K., Xia, G.-S., & Bai, X. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2974745 · Cited by 1,014
Self-citationEfficient and Accurate Arbitrary-Shaped Text Detection With Pixel Aggregation Network
Wang, W., Xie, E., Song, X., Zang, Y., Wang, W., Lu, T., Yu, G., & Shen, C. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00853 · Cited by 632
Scene Text Detection and Recognition: The Deep Learning Era
Long, S., He, X., & Yao, C. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01369-0 · Cited by 527
Self-citationMask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
Lyu, P., Liao, M., Yao, C., Wu, W., & Bai, X. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01264-9_5 · Cited by 522
Self-citationPAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text
Wang, W., Xie, E., Li, X., Liu, X., Liang, D., Zhibo, Y., Lu, T., & Shen, C. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3077555 · Cited by 140
Metadata
- Authors
- Lyu, P., Yao, C., Wu, W., Yan, S., & Bai, X.
- Venue
- 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2018-06
- Pages
- 7553-7563
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2963840241
- Cited by
- 389
- References
- 53
- FWCI
- 19.38
- Type
- conference paper
- Language
- en
- Open access
- green
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