Skip to content

Latest commit

 

History

History
49 lines (33 loc) · 1.12 KB

README.md

File metadata and controls

49 lines (33 loc) · 1.12 KB
Raw

Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer

The paper has been accepted by ICPR 2022.

Training Set

链接：https://pan.baidu.com/s/18cZ-abLH7Aj8019qiRmnig 提取码：1o95

Testing Set

链接：https://pan.baidu.com/s/10DTlZFEHoXIsdMRgqdRsyA 提取码：6rcd

PVT backbone

链接：https://pan.baidu.com/s/1D4hjFBNjMFbJTD5_Ra_1Kw 提取码：xc84

Parameters

链接：https://pan.baidu.com/s/1NHV0eYQ_waB9Epj_3u3FyQ 提取码：rlcw

Code

链接：https://pan.baidu.com/s/1pXyDq9IMG4K-29mzrCDH7A 提取码：k1yx

Result Map

链接：https://pan.baidu.com/s/15RP5Kynt4utg9jfWkDNGuw 提取码：db3v

Citation

If you find the information useful, please consider citing:

@inproceedings{liu2022boosting,
  title={Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer},
  author={Liu, Zhengyi and Zhang, Zhili and Tan, Yacheng and Wu, Wei},
  booktitle={2022 26th International Conference on Pattern Recognition (ICPR)},
  pages={140--146},
  year={2022},
  organization={IEEE}
}

If you have any question, please email liuzywen@ahu.edu.cn