Object Detection in VHR Image Using Transfer Learning with Deformable Convolution
Zeyu Cao, Xiaorun Li, Liaoying Zhao · 2019
In the field of deep learning, finetuning the pretrained networks to get a good classifier is a common way of transfer learning. Unlike the traditional way, we insert deformable convolutional layers into the pretrained networks, and finetune the new networks. As a result, we find it performs as well as the normal one in classification, and when we construct a plane detection pipeline based on the two classifiers respectively, the one with deformable convolution shows a better result than the other.