- Workshop: Few-Shot Learning-Based High-speed Railway Catenary Image Detection and Analysis
- Workshop: 3D Point Cloud Processing, Analysis, and Communication (PC-PAC)
Dataset
We provide a set of training set and validation set of catenary inspection images. The training set and validation set include 50 defect images of high-speed railway catenary and annotation information in PASCAL VOC format. The testing set is not open and consists of 10 catenary defect images. We will test the codes of the participating teams on this data set. The ranking criterion will be the ranking of the average accuracy (mAP) of the testing set.
Training set and validation set：
Google drive：
https://drive.google.com/file/d/1YZO5JGpKd9_raS7NYQl3eSllonXu0Bcu/view?usp=sharing
Baiduyun：
https://pan.baidu.com/s/1Uh1cKRMaxLgEI_kfhygUyg，password：720p 。
Guide
1 Time
- May 1 Release the challenge
- June 20 Registration deadline
- July 20 Deadline for code submission
- July 20 Announce results
- August 6-8 Awards during the ICIG 2021 conference
2 Awards
（1）Award certificate
（2）Bonus
（3）A paper in a cooperative international journal
3 Submit procedure
Participants will send the code (with readme) of the object detection algorithm to the mail cuijing@bjtu.edu.cn.
4 Attention
You guarantee that your submission is your own original work, otherwise the results will be cancelled;
It is strictly forbidden to use other data sets for supervised or unsupervised training.
Organizing Committee
Department: State Key Lab of Rail Traffic Control & Safety (Beijing Jiaotong University)
Chairman: Professor Qin Yong, Professor Jia Limin
Members: Xie Zhengyu, Ma Xiaoping, Wu Yunpeng, Cao Zhiwei, Cui Jing
Contact: Cao Zhiwei (zhiwei@bjtu.edu.cn), Cui Jing (cuijing@bjtu.edu.cn)
Organizing Committee：State Key Lab of Rail Traffic Control & Safety (Beijing Jiaotong University) has long been engaged in the research and application of rail transit safety technology based on image processing. It has accumulated a wealth of academic research results and field application experience, and has accumulated a wealth of field data, which can be used in this challenge. The team participated in the 2018 CVPR image dehazing challenge and the 2018 ChinaMM image dehazing competition. They won the second and third place respectively and have rich experience in participating. In addition, the team has hosted many international conferences such as EITRT and organized ICIG competitions, and has rich conference and competition organization experience.
If you have any questions about this challenge, please send an email to zhiwei@bjtu.edu.cn.