6 citations · 12 across the 6 of their papers we have counts for
6 papers
ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration
Chi-Wei Hsiao, Yu-Lun Liu, Cheng-Kun Yang +3
While recent works on blind face image restoration have successfully produced impressive high-quality (HQ) images with abundant details from low-quality (LQ) input images, the gene…
Denoising Likelihood Score Matching for Conditional Score-based Data Generation
Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng +6
Many existing conditional score-based data generation methods utilize Bayes' theorem to decompose the gradients of a log posterior density into a mixture of scores. These methods f…
Bridging Unsupervised and Supervised Depth from Focus via All-in-Focus Supervision
Ning-Hsu Wang, Ren Wang, Yu-Lun Liu +4
Depth estimation is a long-lasting yet important task in computer vision. Most of the previous works try to estimate depth from input images and assume images are all-in-focus (AiF…
CLCC: Contrastive Learning for Color Constancy
Yi-Chen Lo, Chia-Che Chang, Hsuan-Chao Chiu +4
In this paper, we present CLCC, a novel contrastive learning framework for color constancy. Contrastive learning has been applied for learning high-quality visual representations f…
Explorable Tone Mapping Operators
Chien-Chuan Su, Ren Wang, Hung-Jin Lin +4
Tone-mapping plays an essential role in high dynamic range (HDR) imaging. It aims to preserve visual information of HDR images in a medium with a limited dynamic range. Although ma…
Learning Camera-Aware Noise Models
Ke-Chi Chang, Ren Wang, Hung-Jin Lin +4
Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications. While most previous works adopt statistical noise models, real-world n…