You're currently viewing an old version of this dataset. To see the current version, click here.

Sampling Equivariant Self-attention Networks for Object Detection in Aerial Images

Object detection in aerial images has greater rotational and scale variations because of the overhead image capture, which requires the detection model to more flexibly handle geometric transformations.

Data and Resources

This dataset has no data

Cite this as

Guo-Ye Yang, Xiang-Li Li, Ralph R. Martin, Shi-Min Hu (2024). Dataset: Sampling Equivariant Self-attention Networks for Object Detection in Aerial Images. https://doi.org/10.57702/67iwxwuj

Private DOI This DOI is not yet resolvable.
It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.2111.03420
Author	Guo-Ye Yang
More Authors	Xiang-Li Li Ralph R. Martin Shi-Min Hu
Homepage	https://arxiv.org/abs/1506.02025