SIVED is a SAR image dataset for vehicle detection using Ka, Ku, and X bands of data. Rotatable bounding box annotations were employed to improve positioning accuracy.
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Raw Data
Data Source Band Polarization Resolution FARAD Sandia National Laboratory Ka/X VV/HH 0.1m×0.1m MiniSAR Sandia National Laboratory Ku - 0.1m×0.1m MSTAR U.S. Air Force X HH 0.3m×0.3m -
Statistics
Scene Train Valid Test Total number of chips urban 578 72 71 721 1044 MSTAR 259 32 32 323 number of vehicles urban 5417 710 718 6845 12013 MSTAR 4144 512 512 5168 -
Annotation
XML (reference PASCAL VOC) and TXT (reference DOTA)
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File Structure
If you feel the dataset is useful, please cite as the following format.
@Article{rs15112825,
AUTHOR = {Lin, Xin and Zhang, Bo and Wu, Fan and Wang, Chao and Yang, Yali and Chen, Huiqin},
TITLE = {SIVED: A SAR Image Dataset for Vehicle Detection Based on Rotatable Bounding Box},
JOURNAL = {Remote Sensing},
VOLUME = {15},
YEAR = {2023},
NUMBER = {11},
ARTICLE-NUMBER = {2825},
URL = { https://www.mdpi.com/2072-4292/15/11/2825 },
ISSN = {2072-4292},
DOI = {10.3390/rs15112825}
}
