1 citations · 1 across the 3 of their papers we have counts for
7 papers
Enhancing Underwater Light Field Images via Global Geometry-aware Diffusion Process
Yuji Lin, Qian Zhao, Zongsheng Yue +2
This work studies the challenging problem of acquiring high-quality underwater images via 4-D light field (LF) imaging. To this end, we propose GeoDiff-LF, a novel diffusion-based…
A Data-driven Loss Weighting Scheme across Heterogeneous Tasks for Image Denoising
Xiangyu Rui, Xiangyong Cao, Xile Zhao +2
In a variational denoising model, weight in the data fidelity term plays the role of enhancing the noise-removal capability. It is profoundly correlated with noise information, whi…
Layout-Guided Controllable Pathology Image Generation with In-Context Diffusion Transformers
Yuntao Shou, Xiangyong Cao, Qian Zhao +1
Controllable pathology image synthesis requires reliable regulation of spatial layout, tissue morphology, and semantic detail. However, existing text-guided diffusion models offer…
Generative Latent Kernel Modeling for Blind Motion Deblurring
Chenhao Ding, Jiangtao Zhang, Zongsheng Yue +3
Deep prior-based approaches have demonstrated remarkable success in blind motion deblurring (BMD) recently. These methods, however, are often limited by the high non-convexity of t…
Enhancing Underwater Imaging with 4-D Light Fields: Dataset and Method
Yuji Lin, Junhui Hou, Xianqiang Lyu +2
In this paper, we delve into the realm of 4-D light fields (LFs) to enhance underwater imaging plagued by light absorption, scattering, and other challenges. Contrasting with conve…
Singular Value Fine-tuning for Few-Shot Class-Incremental Learning
Zhiwu Wang, Yichen Wu, Renzhen Wang +4
Class-Incremental Learning (CIL) aims to prevent catastrophic forgetting of previously learned classes while sequentially incorporating new ones. The more challenging Few-shot CIL…