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Geometry Normalization Networks for Accurate Scene Text Detection (iccv 2019)

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GNNets

Now in experimental release, suggestions welcome.

Paper

Youjiang Xu*,  Jiaqi Duan*, Zhanghui Kuang§, Xiaoyu Yue, Hongbin Sun, Yue Guan, Wei Zhang. "Geometry Normalization Networks for Accurate Scene Text Detection" . [Paper]. In ICCV 2019.

@InProceedings{Xu_2019_Geometry,
author = {Xu, Youjiang and Duan, Jiaqi and Kuang, Zhanghui and Yue, Xiaoyu and Sun, Hongbin and Guan, Yue and Zhang, Wei},
title = {Geometry Normalization Networks for Accurate Scene Text Detection},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {Oct},
year = {2019}
}
  • Note that * means authors contributed equally, § means the corresponding author.

Framework

The framework of the proposed Geometry Normalization Networks.

  • The framework of the proposed Geometry Normalization Networks. The feature maps extracted by the backbone are fed into the Geometry Normalization Module (GNM) with multi-branches, each of which is composed of one Scale Normalization Unit (SNU) $\mathcal{F}^s$ and Orientation Normalization Unit (ONU) $\mathcal{F}^o$. There are two different scale normalization units ($\mathcal{S}, \mathcal{S}_\frac{1}{2} $) and four orientation normalization units ($\mathcal{O}, \mathcal{O}_r, \mathcal{O}f, \mathcal{O}{r+f}$). With different combinations of SNU and ONU, GNM generates different geometry normalized feature maps, which are fed into one shared text detection header.

The Rotated ICDAR 2015

  • The Rotated ICDAR 2015 Benchmark could be download form here

Todo List

  • update model performance
  • add rotated ICDAR 2015 benchmark dataset

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Geometry Normalization Networks for Accurate Scene Text Detection (iccv 2019)

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