5 papers · 1 filter
One-Step Effective Diffusion Network for Real-World Image Super-Resolution
Rongyuan Wu, Lingchen Sun, Zhiyuan Ma +1
The pre-trained text-to-image diffusion models have been increasingly employed to tackle the real-world image super-resolution (Real-ISR) problem due to their powerful generative i…
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,…
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…
SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution
Rongyuan Wu, Tao Yang, Lingchen Sun +3
Owe to the powerful generative priors, the pre-trained text-to-image (T2I) diffusion models have become increasingly popular in solving the real-world image super-resolution proble…
NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge
Jie Liang, Radu Timofte, Qiaosi Yi +6
In this paper, we review the NTIRE 2024 challenge on Restore Any Image Model (RAIM) in the Wild. The RAIM challenge constructed a benchmark for image restoration in the wild, inclu…