mmocr/configs/textdet/fcenet
Tong Gao 7571763376
[Refactor] Use MMOCR's registry (#436)
* [Refactor] Use MMOCR's registry

1. Define MMOCR's registries as a child of MMDet's
2. Register all models to MMOCR's own registries
3. Modify some model configs so that some models in MMDet can be
   correctly located
4. Remove some outdated demo scripts

* add detectors
2021-08-19 19:17:15 +08:00
..
README.md fix fcenet readme (#270) 2021-06-09 20:03:16 +08:00
fcenet_r50_fpn_1500e_icdar2015.py [Refactor] Use MMOCR's registry (#436) 2021-08-19 19:17:15 +08:00
fcenet_r50dcnv2_fpn_1500e_ctw1500.py [Refactor] Use MMOCR's registry (#436) 2021-08-19 19:17:15 +08:00
metafile.yml update metafile (#228) 2021-05-22 16:10:21 +08:00

README.md

Fourier Contour Embedding for Arbitrary-Shaped Text Detection

Introduction

[ALGORITHM]

@InProceedings{zhu2021fourier,
      title={Fourier Contour Embedding for Arbitrary-Shaped Text Detection},
      author={Yiqin Zhu and Jianyong Chen and Lingyu Liang and Zhanghui Kuang and Lianwen Jin and Wayne Zhang},
      year={2021},
      booktitle = {CVPR}
      }

Results and models

CTW1500

Method Backbone Pretrained Model Training set Test set #epochs Test size Recall Precision Hmean Download
FCENet ResNet50 + DCNv2 ImageNet CTW1500 Train CTW1500 Test 1500 (736, 1080) 0.828 0.875 0.851 model | log

ICDAR2015

Method Backbone Pretrained Model Training set Test set #epochs Test size Recall Precision Hmean Download
FCENet ResNet50 ImageNet IC15 Train IC15 Test 1500 (2260, 2260) 0.819 0.880 0.849 model | log