Robust ReadingCompetition
Challenges

method: FOTS_v22018-01-22

Authors: Xuebo Liu, Ding Liang, Junjie Yan

Description: FOTS_v2 improves the performance on long text, such as Chinese.

method: FOTS2018-01-22

Authors: Xuebo Liu, Ding Liang, Shi Yan, Dagui Chen, Yu Qiao, Junjie Yan

Description: A unified end-to-end trainable Fast Oriented Text Spotting (FOTS) network for simultaneous detection and recognition, sharing computation and visual information among the two complementary tasks.

method: SARI_FDU_RRPN_v12017-06-29

Authors: Jianqi Ma, Weiyuan Shao, Yingbin Zheng, Hong Wang, Li Wang, Hao Ye, Xiangyang Xue, Shanghai Advanced Research Institute, CAS & Fudan University,

Description: A Rotation Region Proposal Network (RRPN) [8] is designed to generate inclined proposals with text orientation angle information. The angle information is used for bounding box regression to detect accurately oriented text proposals. The rotated region-of-interest pooling layer projects the proposals to a feature map for a text region classifier.

[8]: J. Ma, W. Shao, H. Ye, L. Wang, H. Wang, Y. Zheng, and X. Xue, “Arbitrary-oriented scene text detection via rotation proposals,” CoRR, vol. abs/1703.01086, 2017.

Ranking Table

Description Paper Source Code
DateMethodAverage PrecisionPrecisionRecallHmean
2018-01-22FOTS_v259.93%83.06%65.61%73.31%
2018-01-22FOTS56.95%81.86%62.30%70.75%
2017-06-29SARI_FDU_RRPN_v150.33%71.17%55.50%62.37%

Ranking Graphic

Ranking Graphic