In disaster zones, especially in developing countries, maps and accessibility information are crucial for crisis response. We would like to pose the challenge of automatically extracting roads and street networks from satellite images.
The problem is a binary classification problem. Each input is a satellite image. You must predict a mask for the input, i.e., a binary image of the same height and width as the input image,
There are 2 phases:
You only need to submit the prediction results (no code). However you need to submit your a short paper of 3 pages (+1 page for references) before May 1st to be eligible for the final phase. We will evaluate your methodology and your results in parallel. Paper submission is open at https://cmt3.research.microsoft.com/DeepGlobe2018 and please use the CVPR paper template.
The submissions are evaluated using the IoU (Intersection over Union) metric.
To jump start the thought process and the implementation, you can take a look at some open papers below:
Start: March 1, 2018, 6 p.m.
Description: Directly submit results on validation and/or test data; feedback is provided on the validation set only.
Start: May 1, 2018, midnight
Description: The last submission from the previous phase is automatically cloned and used to compute the final score. The results on the test set will be revealed when the organizers make them available.
May 15, 2018, 11:59 p.m.
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