CHANGE DETECTION IN REMOTE SENSING IMAGES USING CONDITIONAL ADVERSARIAL NETWORKS
Keywords: Change Detection, Database, Deep Convolutional Neural Networks, Generative Adversarial Networks
Abstract. We present a method for change detection in images using Conditional Adversarial Network approach. The original network architecture based on pix2pix is proposed and evaluated for difference map creation. The paper address three types of experiments: change detection in synthetic images without objects relative shift, change detection in synthetic images with small relative shift of objects, and change detection in real season-varying remote sensing images.