Robust ReadingCompetition
Challenges

method: CLOVA-AI / PAPAGO2018-07-03

Authors: Youngmin Baek, Bado Lee, Hwalsuk Lee

Description: Character-level text detection based on weakly-supervised learning. Multi-scale experiment result. CLOVA-AI team, Naver Corp.  (Paper in preparation)

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: FOTS_v22018-01-22

Authors: Xuebo Liu, Ding Liang, Junjie Yan

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

Ranking Table

Description Paper Source Code
DateMethodAverage PrecisionPrecisionRecallHmean
2018-07-03CLOVA-AI / PAPAGO31.68%50.17%65.31%56.75%
2018-01-22FOTS49.09%49.65%66.18%56.74%
2018-01-22FOTS_v246.29%47.58%66.08%55.33%
2018-05-18PSENet_NJU_ImagineLab (single-scale)30.21%45.44%68.28%54.57%
2018-03-12ATL Cangjie OCR56.17%42.20%71.88%53.18%
2017-06-28SCUT_DLVClab138.59%45.80%58.24%51.27%
2017-11-09EAST++29.75%43.27%62.30%51.07%
2017-06-29SARI_FDU_RRPN_v124.45%32.19%50.76%39.40%
2017-06-28SARI_FDU_RRPN_v030.92%28.94%57.72%38.55%
2017-06-30TH-DL20.68%30.16%35.78%32.73%
2017-06-30Sensetime OCR44.78%17.11%68.68%27.39%
2017-06-30linkage-ER-Flow4.02%10.71%21.99%14.40%

Ranking Graphic

Ranking Graphic