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Single-frame InfraRed Small Target-V2 (SIRST-V2) Benchmark

A dataset proposed in "One-Stage Cascade Refinement Networks for Infrared Small Target Detection"

Dataset Description

SIRST-V2 is a dataset specially constructed for single-frame infrared small target detection, in which the images are selected from thousands of infrared sequences for different scenarios.

Annotation formats available:

• bounding box;
• semantic segmentation;
• normalized contrast (produced when data loading).

Citation

Please cite our paper in your publications if our work helps your research. BibTeX reference is as follows.

@article{TGRS23OSCAR,
  author    = {Yimian Dai and Xiang Li and Fei Zhou and Yulei Qian and Yaohong Chen and and Jian Yang,
  title   = {{One-Stage Cascade Refinement Networks for Infrared Small Target Detection}},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  pages   = {1--17},
  year    = {2023},
}

@inproceedings{dai21acm,
  title   =  {Asymmetric Contextual Modulation for Infrared Small Target Detection},
  author  =  {Yimian Dai and Yiquan Wu and Fei Zhou and Kobus Barnard},
  booktitle =  {{IEEE} Winter Conference on Applications of Computer Vision, {WACV} 2021}
  year    =  {2021}
}

@article{TGRS21ALCNet,
  author    = {{Dai}, Yimian and {Wu}, Yiquan and {Zhou}, Fei and {Barnard}, Kobus},
  title   = {{Attentional Local Contrast Networks for Infrared Small Target Detection}},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  pages   = {1--12},
  year    = {2021},
}