Advancing Weakly-Supervised Change Detection in Satellite Images via Adversarial Class Prompting
通过对抗性类别提示推进卫星图像弱监督变化检测
机构 * State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University(信息工程测绘遥感国家重点实验室,武汉大学) ; School of Computer Science and Technology, Anhui University(计算机科学与技术学院,安徽大学) ; Graduate School of Frontier Sciences, University of Tokyo(前沿科学研究院,东京大学) ; Institute of Geodesy and Photogrammetry, ETH Zürich(测绘学研究院,苏黎世联邦理工学院) ; Department of Computer Science, Stanford University(计算机科学系,斯坦福大学)
AI总结 提出对抗性类别提示方法,通过对抗性扰动和原型校正提升卫星图像弱监督变化检测性能。
Comments Accepted by IEEE Transactions on Image Processing