IARPA Functional Map of the World Challenge | Deadline 12.31.17
Intelligence analysts, policy makers, and first responders around the world rely on geospatial land use data to inform crucial decisions about global defense and humanitarian activities. Historically, analysts have manually identified and classified geospatial information by comparing and analyzing satellite images, but that process is time consuming and insufficient to support disaster response.
The Functional Map of the World (fMoW) Challenge seeks to foster breakthroughs in the automated analysis of overhead imagery by harnessing the collective power of the global data science and machine learning communities. The challenge will publish one of the largest publicly available satellite-image datasets to date, with more than one million points of interest from around the world. The dataset contains satellite-specific metadata that researchers can exploit to build a competitive algorithm that classifies facility, building, and land use.
Be Part of the Innovation
IARPA is conducting this Challenge to invite the broader research community of industry and academia, with or without experience in deep learning and computer vision analysis, to participate in a convenient, efficient and non-contractual way. Participants will develop algorithms that scan satellite data to identify functions based on multiple reference sources, such as overhead and ground-based images, digital elevation data, existing well-understood image collections, surface geology, geography, and cultural information. The goals and objectives of this Challenge are to:
- Promote and benchmark deep learning applications for geospatial data
- Stimulate various communities to develop and enhance automation for image/video geolocation data
- Cultivate and sustain an ongoing collaborative community dedicated to this technology and research
Challenge Opens Sep 2017 Register for the challenge at Topcoder.com/fmow/.
Datasets & Training
Jul - Oct 2017 IARPA has released a large satellite imagery dataset with training, validation, and testing imagery subsets to support the fMoW Challenge. The visualization tool and benchmark example can be found here. The testing and training data are availabe for download via two options: 1) Amazon Web Services (AWS) and 2) BitTorrent.
Provisional Scoring Sep 2017
Provisional scoring will be based on your submission of results against the test set and will be evaluated by the Topcoder Marathon test system. Scoring will utilize an algorithm that calculates an F-score for each category and then uses a weighted-average of these scores to determine an overall F-score. Your provisional score will be displayed on the Provisional Leaderboard.
The top 10 competitors, according to the provisional scores at the end of the challenge, will be invited to the final testing round. For a full description of the provisional and final scoring rules and criteria, please visit the registration site.
All participants will have access to IBM Watson and IBM Bluemix for 90 days during the challenge (though these are not required and we welcome all types of solutions for the challenge). Top competitors will periodically receive access to AWS cloud computing resources to improve their algorithms, more information can be found in the TopCoder forums.
Final Submission December 31, 2017
The challenge submission period will end. The final score shown on the Provisional Leaderboard at the end of the challenge will be used to determine solver rankings going into the final evaluation. The top 10 algorithms will be scored against a hidden data set, and the top scoring solutions will be validated by the IARPA team for award. Final scores will be posted to the leaderboard on Topcoder and shared through official IARPA communications.
Awards & Recognition Feb 2018
The challenge winners will be invited to present their solutions to IARPA and other key leaders in the Government at a workshop in Washington, DC, and cash awards will be distributed to winners. Final public communication about winners will take place during this day-long workshop.