activity
20242026
most citedImplicit Image-to-Image Schrodinger Bridge for Image Restoration

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2026

Coronary Mask Guided Registration for Continuous Time 4D Cardiac CT Dataset Construction

Yuang Wang, Shuo Wang, Changyu Chen +12

Objective: Clinical cardiac CT multiphase reconstructions generally provide acceptable image quality in end-diastole (ED) or end-systole (ES) phases, but in other phases may exhibi…

cs.CV2025

Projection Embedded Diffusion Bridge for CT Reconstruction from Incomplete Data

Yuang Wang, Pengfei Jin, Siyeop Yoon +6

Reconstructing CT images from incomplete projection data remains challenging due to the ill-posed nature of the problem. Diffusion bridge models have recently shown promise in rest…

cs.CV2025

Noise Controlled CT Super-Resolution with Conditional Diffusion Model

Yuang Wang, Siyeop Yoon, Rui Hu +6

Improving the spatial resolution of CT images is a meaningful yet challenging task, often accompanied by the issue of noise amplification. This article introduces an innovative fra…

cs.CV2024

An Ordinary Differential Equation Sampler with Stochastic Start for Diffusion Bridge Models

Yuang Wang, Pengfei Jin, Li Zhang +3

Diffusion bridge models have demonstrated promising performance in conditional image generation tasks, such as image restoration and translation, by initializing the generative pro…

eess.IV2024

Measurement Embedded Schrödinger Bridge for Inverse Problems

Yuang Wang, Pengfei Jin, Siyeop Yoon +4

Score-based diffusion models are frequently employed as structural priors in inverse problems. However, their iterative denoising process, initiated from Gaussian noise, often resu…

eess.IV2024★ 1 cited

Implicit Image-to-Image Schrodinger Bridge for Image Restoration

Yuang Wang, Siyeop Yoon, Pengfei Jin +8

Diffusion-based models have demonstrated remarkable effectiveness in image restoration tasks; however, their iterative denoising process, which starts from Gaussian noise, often le…