19 citations · 54 across the 17 of their papers we have counts for
22 papers · 1 filter
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…
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…
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…
Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction
Yuntao Shou, Peiqiang Yan, Xingjian Yuan +3
In recent years, histopathological whole slide image (WSI)- based survival analysis has attracted much attention in medical image analysis. In practice, WSIs usually come from diff…
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…
Blind Image Deconvolution by Generative-based Kernel Prior and Initializer via Latent Encoding
Jiangtao Zhang, Zongsheng Yue, Hui Wang +2
Blind image deconvolution (BID) is a classic yet challenging problem in the field of image processing. Recent advances in deep image prior (DIP) have motivated a series of DIP-base…