HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation

With the development of satellite technology, up to date imaging mode of synthetic aperture radar (SAR) satellite can provide higher resolution SAR imageries, which benefits ship detection and instance segmentation. Meanwhile, object detectors based on convolutional neural network (CNN) show high performance on SAR ship detection even without land-ocean segmentation; but with respective shortcomings, such as the relatively small size of SAR images for ship detection, limited SAR training samples, and inappropriate annotations, in existing SAR ship datasets, related research is hampered. To promote the development of CNN based ship detection and instance segmentation, we have constructed a High-Resolution SAR…

• NN
  National Natural Science Foundation of China

  Award: 61501098
• CU
  Chongqing University
• CP
  China Postdoctoral Science Foundation

  Award: 2015M570778
• CU
  Chongqing University of Posts and Telecommunications
• UO
  University of Electronic Science and Technology of China
• NU
  North University of China
• NK
  National Key Research and Development Program of China

  Award: 2017-YFB0502700