GCD-DDPM是一个生成模型,由两个阶段组成,即前向扩散阶段和反向扩散阶段。 在前向过程中,变化检测标签x0逐渐加入高斯噪声,通过一系列步骤T实现。 在反向扩散阶段,训练一个神经网络作为噪声预测器来逆转噪声过程,并随后恢复原始数据。 A. Diffusion Process of GCD-DDPM ...
Leveraging the variational inference (VI) procedure, GCD-DDPM can adaptively re-calibrate the CD results through an iterative inference process, while accurately distinguishing subtle and irregular changes in diverse scenes. Finally, a Noise Suppression-based Semantic Enhancer (NSSE) is specifically ...