AMRNet: Chips Augmentation in Aerial Images Object Detection

Understand

Object detection in aerial images is a challenging task due to the following reasons: (1) objects are small and dense relative to images; (2) the object scale varies in a wide range; (3) the number of object in different classes is imbalanced.

• Many current methods adopt cropping idea: splitting high resolution images into serials subregions (chips) and detecting on them.
• However, some problems such as scale variation, object sparsity, and class imbalance exist in the process of training network with chips.
• In this work, three augmentation methods are introduced to relieve these problems.