Manifold Constraint Regularization for Remote Sensing Image Generation

arXiv:2305.19507v3 Announce Type: replace
Abstract: Generative Adversarial Networks (GANs) have shown notable accomplishments in remote sensing domain. However, this paper reveals that their performance on remote sensing images falls short when compared to their impressive results with natural images. This study identifies a previously overlooked issue: GANs exhibit a heightened susceptibility to overfitting on remote sensing images.To address this challenge, this paper analyzes the characteristics of remote sensing images and proposes manifold constraint regularization, a novel approach that tackles overfitting …

abstract adversarial arxiv cs.cv domain eess.iv gans generative generative adversarial networks however image image generation images issue manifold natural networks paper performance regularization results sensing study type