Prize Challenges

Functional Map of the World (fMoW) Challenge

Can you build algorithms to classify facility, building, and land use from satellite imagery? The functional Map of the World (fMoW) Challenge invites solvers from around the world to develop deep learning and other automated techniques to classify points of interest from satellite imagery. The goal of the challenge is to promote research in object identification and classification to automatically identify facility, building, and land use.


Who We Are: The Intelligence Advanced Research Projects Activity (IARPA), within the Office of the Director of National Intelligence (ODNI), focuses on high-risk, high-payoff research programs to tackle difficult challenges of the agencies and disciplines in the Intelligence Community. IARPA Challenges invite experts from the broader research community of academia and industry, and developers to participate in IARPA research in a convenient, efficient, and non-contractual way.

What We’re Doing: FMoW invites experts from across the government, academia, industry, and developer communities—with or without experience in automated image analysis—to create fast and accurate classification algorithms for building and land use. FMoW Challenge will provide a satellite imagery dataset with one million points of interest annotated to researchers and entrepreneurs, enabling them to better their methods for understanding satellite imagery through novel learning frameworks and multi-modal fusion techniques. Based on the data provided, participants will be asked to generate an algorithm to classify building and land use in the provided images.

Why We're Doing This: Creating algorithms to accurately label parts of images has been proven to be a notoriously difficult problem. The last couple of years have seen landmark advances in deep learning provide great improvements in both localization and classification of objects within scenes.  IARPA is interested to know if those techniques (or perhaps newly developed techniques) can be used to label satellite imagery accurately.  A Challenge provides a cost-effective way to carry out such research. 

Who Should Participate: Anyone over age 18 is welcome to participate, and participants have the option to form teams. Specifically, we’re looking for solutions from anyone who thinks they might have a way of addressing this problem, including data scientists, geospatial imagery analysts, computer programmers, and even (or especially) experts in disciplines we haven’t yet considered. Certain individuals and groups with existing agreements with IARPA may not be eligible for cash prizes, but may compete for standing on the leaderboard and other non-monetary incentives. Participants will join a global community working to benchmark research and foster innovation in automated imagery analysis through crowdsourcing.

Why Should You Participate? This challenge gives you a chance to join a community of leading experts to advance your research, contribute to global security and humanitarian activities, and win cash prizes:

  • Network with collaborators and experts to advance your research
  • Gain recognition for your work and your program
  • Win prizes from a total prize purse of $100,000

Throughout the challenge, an online leaderboard will display solvers’ rankings and accomplishments, giving you opportunities to have your work viewed and appreciated by leaders from the industry, government and academia.

When We’re Doing This: The challenge will kick off Summer 2017. 

When does pre-registration begin? July 2017
When does the challenge launch? September 2017
Where to learn more about the challenge, including rules, criteria and eligibility requirements:
Where do solvers register?
How do I stay connected to get information on when the microsite and challenge registration opens? Send us an email at and we will add you to our mailing list.
When does the challenge end? December 2017

For more information, see the press release, or email

Related Program(s):