6 citations · 12 across the 3 of their papers we have counts for
4 papers · 1 filter
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…