3 papers
eess.IV2024
Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-Resolution
Lingchen Sun, Rongyuan Wu, Jie Liang +3
The generative priors of pre-trained latent diffusion models (DMs) have demonstrated great potential to enhance the visual quality of image super-resolution (SR) results. However,…
eess.IV2024
Perception-Distortion Balanced Super-Resolution: A Multi-Objective Optimization Perspective
Lingchen Sun, Jie Liang, Shuaizheng Liu +2
High perceptual quality and low distortion degree are two important goals in image restoration tasks such as super-resolution (SR). Most of the existing SR methods aim to achieve t…
eess.IV2024
Deep Variational Network Toward Blind Image Restoration
Zongsheng Yue, Hongwei Yong, Qian Zhao +3
Blind image restoration (IR) is a common yet challenging problem in computer vision. Classical model-based methods and recent deep learning (DL)-based methods represent two differe…