Search Results for author:
Found 4 papers, 4 papers with code
Improving the Stability of Diffusion Models for Content Consistent Super-Resolution
To improve the stability of diffusion prior-based SR, we propose to employ the diffusion models to refine image structures, while employing the generative adversarial training to enhance image fine details.
Perception-Distortion Balanced Super-Resolution: A Multi-Objective Optimization Perspective
High perceptual quality and low distortion degree are two important goals in image restoration tasks such as super-resolution (SR).
SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution
First, we train a degradation-aware prompt extractor, which can generate accurate soft and hard semantic prompts even under strong degradation.
Joint HDR Denoising and Fusion: A Real-World Mobile HDR Image Dataset
In this work, we develop, for the first time to our best knowledge, an HDR image dataset by using mobile phone cameras, namely Mobile-HDR dataset.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
