DOTA: A Large-scale Dataset for Object DeTection in Aerial Images

Gui-Song Xia, Xiang Bai, Jian Ding, Zhen Zhu, Serge Belongie,
Jiebo Luo, Mihai Datcu, Marcello Pelillo, Liangpei Zhang.


  • 2018-08-19We updated the leaderboard. New
  • 2018-06-27You can make comments on the evaluation server page now. New
  • 2018-06-24 All the trained models mentioned in paper were released. You can find it in the Dataset page. New
  • 2018-04-30 The code of Faster-RCNN OBB is released. New
  • 2018-03-20 Fix little bug on gsd of annotation. New
  • 2018-03-16 The registration for ODAI is open now. New
  • 2018-03-14 We updated the results on the baseline algorithms in results page.
  • 2018-03-8 DOTA development kit ia available now. It's helpful to play on DOTA!
  • 2018-02-19 The article of DOTA has been accepted by CVPR'2018.
  • 2018-02-08 ODAI:a contest of object detection in aerial images on ICPR'2018, is now open!
  • 2018-01-27 A problem of annotations is fixed and a new-version annotation has been released.
  • 2018-01-26 DOTA-v1.0 released with all images and oriented bounding box annotations for training and vallidation!


Dota is a large-scale dataset for object detection in aerial images. It can be used to develop and evaluate object detectors in aerial images. We will continue to update DOTA, to grow in size and scope and to reflect evolving real-world conditions. For the DOTA-v1.0, as described in the paper, it contains 2806 aerial images from different sensors and platforms. Each image is of the size in the range from about 800 × 800 to 4000 × 4000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes. These DOTA images are then annotated by experts in aerial image interpretation using 15 common object categories. The fully annotated DOTA images contains 188, 282 instances, each of which is labeled by an arbitrary (8 d.o.f.) quadrilateral.

For more details, refer to the arXiv preprint of DOTA.

Examples of Annotated Images


If you make use of the DOTA dataset, please cite our following paper:

author = {Xia, Gui-Song and Bai, Xiang and Ding, Jian and Zhu, Zhen and Belongie, Serge and Luo, Jiebo and Datcu, Mihai and Pelillo, Marcello and Zhang, Liangpei},
title = {DOTA: A Large-Scale Dataset for Object Detection in Aerial Images},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}


For any problem you have in using DOTA or ODAI, you can join the WeChat group and communicate.

Because the number of WeChat groups exceeds 100, invitations are needed, so the discussion group is moved to the QQ group.

You can also ask questions and comment on the comment area of the evaluation server page now.


If you have any the problem or feedback in using DOTA, please contact

  • Gui-Song Xia at,
  • Xiang Bai at,
  • Jian Ding at,
  • Zhen Zhu at