README.md

March 27, 2024 · View on GitHub

LMOD: A large-scale and multiclass moving object detection dataset for satellite videos

480,332 labels ~ Total.

459,713 Vehicles,

9,390 Aircrafts,

10,536 Ships,

693 Trains.

Our work is expected to contribute to the visual tracking community.

Getting the dataset

:star: The dataset application is very simple and requires only the following two steps:

  • Please fill in this application form.
  • Please send your completed application form to this E-mail address:rs_devotee@163.com.
    When we receive your application, we will reply as soon as possible. Thank you for your support!

Introduction

  • The LMOD dataset is the first satellite video moving multi-object detection dataset with both large-scale and multiclass labeling features. LMOD consists of eight sequences from seven videos.
  • LOMD has a wide range of annotation, the smallest image width is 1500×1160, and the largest image width is 4000×2000. The large range of scenes can better simulate the effect of object detection methods used in real scenes, but at the same time, it brings more challenges for object detection.
  • The LMOD is labeled with 459,713 vehicle objects, 9,390 aircraft objects, 10,536 ship objects and 693 train objects, for a total of 480,332 objects, with each sequence labeled with at least two classes of objects.

Visualization

Data Source

Contact

:mailbox: If you have any questions, please contact rs_devotee@163.com.

For more details check out Here.

Tips :sun_with_face:

If you want to use multi-object detection and tracking or single-object tracking dataset labeled with the OBB (Oriented Bounding Box) method which has orientation information, you can try to use the OODT dataset that we have published before.