91 citations · 274 across the 15 of their papers we have counts for
7 papers · 1 filter
Gene-induced Multimodal Pre-training for Image-omic Classification
Ting Jin, Xingran Xie, Renjie Wan +2
Histology analysis of the tumor micro-environment integrated with genomic assays is the gold standard for most cancers in modern medicine. This paper proposes a Gene-induced Multim…
CopyRNeRF: Protecting the CopyRight of Neural Radiance Fields
Ziyuan Luo, Qing Guo, Ka Chun Cheung +2
Neural Radiance Fields (NeRF) have the potential to be a major representation of media. Since training a NeRF has never been an easy task, the protection of its model copyright sho…
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting
Canyu Zhang, Qing Guo, Xiaoguang Li +4
In this work, we introduce a challenging image restoration task, referred to as SuperInpaint, which aims to reconstruct missing regions in low-resolution images and generate comple…
Enhancing Low-Light Images Using Infrared-Encoded Images
Shulin Tian, Yufei Wang, Renjie Wan +3
Low-light image enhancement task is essential yet challenging as it is ill-posed intrinsically. Previous arts mainly focus on the low-light images captured in the visible spectrum…
The Age of Synthetic Realities: Challenges and Opportunities
João Phillipe Cardenuto, Jing Yang, Rafael Padilha +7
Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of…
Removing Image Artifacts From Scratched Lens Protectors
Yufei Wang, Renjie Wan, Wenhan Yang +3
A protector is placed in front of the camera lens for mobile devices to avoid damage, while the protector itself can be easily scratched accidentally, especially for plastic ones.…
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty Alignment
Kecheng Chen, Jie Liu, Renjie Wan +4
Low-dose computed tomography (LDCT) image reconstruction techniques can reduce patient radiation exposure while maintaining acceptable imaging quality. Deep learning is widely used…