5 citations · 9 across the 5 of their papers we have counts for
5 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…
Self-Supervised Robustifying Guidance for Monocular 3D Face Reconstruction
Hitika Tiwari, Min-Hung Chen, Yi-Min Tsai +5
Despite the recent developments in 3D Face Reconstruction from occluded and noisy face images, the performance is still unsatisfactory. Moreover, most existing methods rely on addi…
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…
Network Space Search for Pareto-Efficient Spaces
Min-Fong Hong, Hao-Yun Chen, Min-Hung Chen +5
Network spaces have been known as a critical factor in both handcrafted network designs or defining search spaces for Neural Architecture Search (NAS). However, an effective space…