Title
IOS-Net: An Inside-to-outside Supervision Network for Scale Robust Text Detection in the wild
Abstract
•We propose an inside-to-outside supervision network to detect text in natural scenes.•Our method can comprehensively tackle the R-scale and S-scale problems.•Our method achieves a state-of-the-art performance on three public benchmarks.•Our method is the best text detector with respect to the speed and F-score trade-off.
Year
DOI
Venue
2020
10.1016/j.patcog.2020.107304
Pattern Recognition
Keywords
DocType
Volume
Text detection,Various sizes,Diverse aspect ratios,Inside-to-outside supervision,Position-sensitive segmentation
Journal
103
Issue
ISSN
Citations 
1
0031-3203
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yuanqiang Cai122.05
Weiqiang Wang2138.65
Yuting Chen300.34
Qixiang Ye491364.51