xView: Objects in Context in Overhead Imagery

نویسندگان

  • Darius Lam
  • Richard Kuzma
  • Kevin McGee
  • Samuel Dooley
  • Michael Laielli
  • Matthew Klaric
  • Yaroslav Bulatov
  • Brendan McCord
چکیده

We introduce a new large-scale dataset for the advancement of object detection techniques and overhead object detection research. This satellite imagery dataset enables research progress pertaining to four key computer vision frontiers.We utilize a novel process for geospatial category detection and bounding box annotation with three stages of quality control. Our data is collected from WorldView-3 satellites at 0.3m ground sample distance, providing higher resolution imagery than most public satellite imagery datasets. We compare xView to other object detection datasets in both natural and overhead imagery domains and then provide a baseline analysis using the Single Shot MultiBox Detector. xView is one of the largest and most diverse publicly available objectdetection datasets to date, with over 1 million objects across 60 classes in over 1,400 km2 of imagery.

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عنوان ژورنال:
  • CoRR

دوره abs/1802.07856  شماره 

صفحات  -

تاریخ انتشار 2018