2 citations · 4 across the 12 of their papers we have counts for
11 papers
Stochastic Generative Plug-and-Play Priors
Chicago Y. Park, Edward P. Chandler, Yuyang Hu +4
Plug-and-play (PnP) methods are widely used for solving imaging inverse problems by incorporating a denoiser into optimization algorithms. Score-based diffusion models (SBDMs) have…
A Unified Framework for Multimodal Image Reconstruction and Synthesis using Denoising Diffusion Models
Weijie Gan, Xucheng Wang, Tongyao Wang +6
Image reconstruction and image synthesis are important for handling incomplete multimodal imaging data, but existing methods require various task-specific models, complicating trai…
Measurement Score-Based MRI Reconstruction with Automatic Coil Sensitivity Estimation
Tingjun Liu, Chicago Y. Park, Yuyang Hu +2
Diffusion-based inverse problem solvers (DIS) have recently shown outstanding performance in compressed-sensing parallel MRI reconstruction by combining diffusion priors with physi…
Kernel Density Steering: Inference-Time Scaling via Mode Seeking for Image Restoration
Yuyang Hu, Kangfu Mei, Mojtaba Sahraee-Ardakan +3
Diffusion models show promise for image restoration, but existing methods often struggle with inconsistent fidelity and undesirable artifacts. To address this, we introduce Kernel…
Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal
Yuyang Hu, Suhas Lohit, Ulugbek S. Kamilov +1
Deep learning has achieved some success in addressing the challenge of cloud removal in optical satellite images, by fusing with synthetic aperture radar (SAR) images. Recently, di…
A Self-supervised Diffusion Bridge for MRI Reconstruction
Harry Gao, Weijie Gan, Yuyang Hu +2
Diffusion bridges (DBs) are a class of diffusion models that enable faster sampling by interpolating between two paired image distributions. Training traditional DBs for image reco…