Image restoration and representation with deep generative models - Wang, Yufei (Nanyang Technological University, 2025)
A fundamental challenge in the realm of computer vision lies in accurately modeling/characterizing image distributions. For example, in high-level vision tasks, better representations of images in the latent space can significantly enhance downstream processes such as image classification and segmentation. Similarly, in image restoration, a more accurate model for the distributions of clean images conditioned on degraded images can yield results with better perceptual quality. However, modeling these distributions is highly challenging due to the high dimensionality of both images and their latent codes.