Challenge Introduction
Colorization is an important step in cartoon production, which turns the black-and-white line drawings of cartoon images into colorful cartoon images. Automatic colorization of black-and-white line drawings can greatly reduce the cost of cartoon production, promote the development of the cartoon industry, and make it easy for non- professional users to create colorful cartoon images. To promote the application of machine learning and deep learning algorithms for automatic coloring, we organized the Colorization for Cartoons challenge, and various excellent methods were encouraged to use.
Our challenge is based on a professional cartoon line drawings dataset, using which various algorithms can test their performance and make a fair comparison with other algorithms.
The main task of the track is to color the input black and white line drawings to generate outstanding colorful cartoon images.
Challenge Organization
Challenge Co-Chairs
- Prof. Tong-Yee Lee, National Cheng-Kung University, Taiwan, China
- Muhammd Nadeem Cheema, COMSATS University Islamabad, Attock campus,Islamabad,Pakistan
E-mail: nadeemcheema.cs@gmail.com
Organizing Team
- Muhammd Nadeem Cheema, COMSATS University Islamabad, Attock campus, Islamabad, Pakistan
- Jin Huang, Wuhan Textile University, Wuhan, China
- Wenqing Zhao, Wuhan Textile University, Wuhan, China
- Xinrong Hu, Wuhan Textile University, Wuhan, China
Challenge Webpage
Challenge Contact
Wenqing Zhao, Wuhan Textile University, Wuhan, China
E-mail: cgi_ccc2023@163.com