3 accepted papers
Large-scale pre-trained diffusion models have been extensively adopted for real-world image Super-Resolution because of their powerful generative priors through textual guidance. However, when super-resolving high-resolution images with patch-wise inference strategy, most existing diffusion-based SR
Hyperspectral image (HSI) reconstruction is about recovering a 3D HSI from its 2D snapshot measurements, to which deep models have become a promising approach. However, most existing studies train deep models on large amounts of organized data, the collection of which can be difficult in many applic…
In last few years, supervised deep learning has emerged as one powerful tool for image denoising, which trains a denoising network over an external dataset of noisy/clean image pairs. However, the requirement on a high-quality training dataset limits the broad applicability of the denoising networks…