Aggregation cross-entropy (ACE: Aggregation Cross-Entropy for Sequence Recognition (CVPR 2019)), for sequence recognition from a brand new perspective. ACE loss only requires only characters and their numbers in the sequence annotation for supervision, which allows it to advance beyond sequence recognition
Dataset | Samples | Description | Release |
---|---|---|---|
MJSynth | 8919257 | Scene text recognition synthetic data set | Link |
SynText | 7266164 | A synthesized by scene text dataset, and the text is cropped from the large image | Link |
Test Set | Instance Number | Note |
---|---|---|
IIIT5K | 3000 | regular |
SVT | 647 | regular |
IC03_860 | 860 | regular |
IC13_857 | 857 | regular |
IC15_1811 | 1811 | irregular |
SVTP | 645 | irregular |
CUTE80 | 288 | irregular |
Test Set | Instance Number | Note |
---|---|---|
IIIT5K | 3000 | regular |
SVT | 647 | regular |
IC03_860 | 860 | regular |
IC13_857 | 857 | regular |
IC15_1811 | 1811 | irregular |
SVTP | 645 | irregular |
CUTE80 | 288 | irregular |
A quick start is to use above lmdb-formatted datasets that contain the full benchmarks for scene text recognition tasks as belows.
Data Type: LMDB
File storage format:
|-- train
| |-- MJ
| |-- ST
|-- validation
| |-- mixture
|-- evaluation
| |-- mixture
Run the following bash command in the command line,
cd .
bash ./train.sh
We provide the implementation of online validation. If you want to close it to save training time, you may modify the startup script to add
--no-validate
command.
cd ../test_scripts
bash ./test_ace.sh
Methods | Regular Text | Irregular Text | Download | ||||||
Name | IIIT5K | SVT | IC03 | IC13 | IC15 | SVTP | CUTE80 | Config | Model |
ACE Loss(Report) | 82.3 | 82.6 | 92.1 | - | - | - | - | - |
- |
ACE Loss | 90.9 | 84.2 | 90.2 | 90.1 | 73.4 | 71.9 | 77.1 | pth BaiduYunPan (Code:brey), Google Drive |
|
Here is the picture for result visualization.
@inproceedings{ACE,
author={Zecheng Xie and Yaoxiong Huang and Yuanzhi Zhu and Lianwen Jin and Yuliang Liu and Lele Xie},
title={Aggregation Cross-Entropy for Sequence Recognition},
booktitle={CVPR2019},
pages={6538--6547},
publisher={Computer Vision Foundation / {IEEE}},
year={2019},
}
This project is released under the Apache 2.0 license
If there is any suggestion and problem, please feel free to contact the author with jianghui11@hikvision.com or chengzhanzhan@hikvision.com.