ACM Multimedia 2024 Grand Challenge Report for Artificial Intelligence Generated Image Detection
The AI Generated Image Detection Challenge, organized by MGTV, invites participants to develop advanced algorithms capable of accurately distinguishing between real and AI-generated images. These images may be created using various cutting-edge techniques, including but not limited to GAN and Stable Diffusion algorithms. Participants are encouraged to utilize open-source datasets or develop their own datasets to train their algorithms. This challenge presents a unique opportunity to enhance the field of AI-generated image detection, particularly in improving the algorithm's generalization capabilities to identify unknown and emerging samples. For more details and resources, please visit our official website (https://challenge.ai.mgtv.com/#/track/24).
Authors
- Jin Chen (ORCID: https://orcid.org/0009-0003-7984-8054)
- Yizhen Lao (ORCID: https://orcid.org/0000-0002-6284-1724)
- Han Qi
- Shien Song (ORCID: https://orcid.org/0009-0005-0324-243X)
- Yifei Xue (ORCID: https://orcid.org/0000-0002-4443-4367)
- Yi Yu (ORCID: https://orcid.org/0009-0004-1485-1567)
- Jie Yang (ORCID: https://orcid.org/0009-0008-2856-2239)
Institutions
- Hunan University (CN)
- China Central Television (CN)
Publication Details
- Published
- 2024-10-26
- DOI
- https://doi.org/10.1145/3664647.3689001
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00