University of Tübingen, Germany
Next-generation, location-based computer vision (CV) applications like augmented reality or autonomous driving require robustly working CV algorithms. Robustness means that algorithms can cope with variability in input data like seasonal and weather-related appearance changes, low-quality data from cheap cameras, or data captured under suboptimal lighting conditions. Producing reliable predictions in such challenging data scenarios and for highly varying, city-scale environments makes a real impact for downstream applications.
To make this impact measurable, we are introducing a novel, city-scale data set called Mapillary Metropolis, available from August 31, 2021. This data set is designed with the goal of creating a completely novel and complex benchmarking paradigm for training and testing computer vision algorithms in the context of semantic 3D map making. Our new data set comprises multiple data modalities at a city-scale size, registered across different representations, and enriched with human- and machine-generated annotations for different object recognition and tracking tasks. These modalities include professional- and consumer-grade street-level images, aerial images, 3D point clouds from street-level LiDAR, aerial LiDAR, and image-based reconstruction (SfM and MVS), and CAD models. All data modalities are aligned based on manual correspondence annotations and ingestion of survey-grade ground control point data. Our data set is designed to take city-scale 3D semantic modeling to the next level by enabling researchers to study shortcomings in current methods including, but not limited to, object recognition and tracking, 3D modeling, depth estimation, relocalization, image retrieval, change detection, sensor-fusion, and so on.
We are soliciting high-quality, aspiring proposals leveraging our novel Metropolis data set to improve basic CV algorithms that use one or preferably multiple data modalities from our data set for improving semantic 3D building.
To foster further innovation in this area, and to deepen our collaboration with academia, Facebook is pleased to invite faculty to respond to this call for research proposals pertaining to the aforementioned topics. We anticipate issuing up to a total of five awards, each in the $50,000 to $100,000 range. Payment will be made to the proposer’s host university as an unrestricted gift, and researchers will be invited to join subsequent workshops and meet-ups.
University of Tübingen, Germany
Czech Technical University in Prague
Stanford University
Applications Are Currently CLosed
Note: The deadline has been extended to Friday, August 27 at 5:00pm AOE.
Areas of interest include, but are not limited to, the following:
Winners will be announced at the ICCV tutorial on Metropolis data set. In-person meetings (post-COVID) will happen in 2022.
You can learn more about the features of the Mapillary Metropolis data set here, starting at the 1:08:30 mark.
For questions related to this RFP, please email Peter Kontschieder pkontschieder@fb.com.
Most of the RFP awards are an unrestricted gift. Because of its nature, salary/headcount could be included as part of the budget presented for the RFP. Since the award/gift is paid to the university, they will be able to allocate the funds to that winning project and have the freedom to use as they need. All Facebook teams are different and have different expectations concerning deliverables, timing, etc. Long story short – yes, money for salary/headcount can be included. It’s up to the reviewing team to determine if the percentage spend is reasonable and how that relates to the decision if the project is a winner or not.
We are flexible, but ideally proposals submitted are single-spaced, Times New Roman, 12 pt font.
Research awards are given year-round and funding years/duration can vary by proposal.
Yes, award funds can be used to cover a researcher’s salary.
One person will need to be the primary PI (i.e., the submitter that will receive all email notifications); however, you’ll be given the opportunity to list collaborators/co-PIs in the submission form. Please note in your budget breakdown how the funds should be dispersed amongst PIs.
Please read these terms carefully before proceeding.
Facebook’s decisions will be final in all matters relating to Facebook RFP solicitations, including whether or not to grant an award and the interpretation of Facebook RFP Terms and Conditions. By submitting a proposal, applicants affirm that they have read and agree to these Terms and Conditions.