Research Challenges

5/6/2024 - 6/30/2024

The objective of this challenge is to develop innovative and robust machine learning or deep learning models that can accurately detect synthetic AI-generated images. Participants will be challenged to build models that can discern between real images, including ones that may have been manipulated or edited using non-AI methods and fully synthetic AI-generated images.

8/1/2024 - 9/30/2024

The objective of this challenge is to develop innovative and robust machine learning or deep learning models that can accurately attribute and classify synthetic AI-generated images to the base model that created them. Participants will be challenged to build models that can attribute AI-generated images to known, publicly available models.

7/1/2025 - 8/31/2025

The SAFE: Synthetic Video Detection Challenge will drive innovation in detecting and attributing synthetic and manipulated video content. It will focus on several critical dimensions of synthetic video detection performance, including generalizability across diverse visual domains, robustness against evolving generative video techniques, and scalability for real-world deployment. As generative video technologies advance rapidly—with increasing accessibility and sophistication of image-to-video, text-to-video, and adversarially optimized pipelines—the need for effective and reliable solutions to authenticate video content has become urgent. We aim to mobilize the research community to address this need and strengthen global efforts in media integrity and trust.