Hyungjin Chung

According to our database, Hyungjin Chung authored at least 38 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fundus Photo Enhancement dataset.

Hyungjin Chung, Se Hie Park, Eui-Sang Chung, Kayoung Yi, Jong Chul Ye

Dataset, June, 2024

ACDC: Autoregressive Coherent Multimodal Generation using Diffusion Correction.

Hyungjin Chung, Dohun Lee, Jong Chul Ye

CoRR, 2024

A Survey on Diffusion Models for Inverse Problems.

Giannis Daras, Hyungjin Chung, Chieh-Hsin Lai, Yuki Mitsufuji, Jong Chul Ye, Peyman Milanfar, Alexandros G. Dimakis, Mauricio Delbracio

CoRR, 2024

Fundus image enhancement through direct diffusion bridges.

Sehui Kim, Hyungjin Chung, Se Hie Park, Eui-Sang Chung, Kayoung Yi, Jong Chul Ye

CoRR, 2024

Amortized Posterior Sampling with Diffusion Prior Distillation.

Abbas Mammadov, Hyungjin Chung, Jong Chul Ye

CoRR, 2024

CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models.

Hyungjin Chung, Jeongsol Kim, Geon Yeong Park, Hyelin Nam, Jong Chul Ye

CoRR, 2024

Objective and Interpretable Breast Cosmesis Evaluation with Attention Guided Denoising Diffusion Anomaly Detection Model.

Sangjoon Park, Yong Bae Kim, Jee Suk Chang, Seo Hee Choi, Hyungjin Chung, Ik-Jae Lee, Hwa Kyung Byun

CoRR, 2024

Prompt-tuning Latent Diffusion Models for Inverse Problems.

Hyungjin Chung, Jong Chul Ye, Peyman Milanfar, Mauricio Delbracio

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems.

Hyungjin Chung, Suhyeon Lee, Jong Chul Ye

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Deep Diffusion Image Prior for Efficient OOD Adaptation in 3D Inverse Problems.

Hyungjin Chung, Jong Chul Ye

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion.

Hyungjin Chung, Eun Sun Lee, Jong Chul Ye

IEEE Trans. Medical Imaging, April, 2023

Regularization by Texts for Latent Diffusion Inverse Solvers.

Jeongsol Kim, Geon Yeong Park, Hyungjin Chung, Jong Chul Ye

CoRR, 2023

Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems.

Riccardo Barbano, Alexander Denker, Hyungjin Chung, Tae-Hoon Roh, Simon Arrdige, Peter Maass, Bangti Jin, Jong Chul Ye

CoRR, 2023

Generative AI for Medical Imaging: extending the MONAI Framework.

Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot, Petru-Daniel Tudosiu, Jessica Dafflon, Virginia Fernandez, Pedro Sanchez, Julia Wolleb, Pedro F. Da Costa, Ashay Patel, Hyungjin Chung, Can Zhao, Wei Peng, Zelong Liu, XueYan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

CoRR, 2023

Fast Diffusion Sampler for Inverse Problems by Geometric Decomposition.

Hyungjin Chung, Suhyeon Lee, Jong Chul Ye

CoRR, 2023

Direct Diffusion Bridge using Data Consistency for Inverse Problems.

Hyungjin Chung, Jeongsol Kim, Jong Chul Ye

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Diffusion Posterior Sampling for General Noisy Inverse Problems.

Hyungjin Chung, Jeongsol Kim, Michael Thompson McCann, Marc Louis Klasky, Jong Chul Ye

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Score-Based Diffusion Models for Bayesian Image Reconstruction.

Michael T. McCann, Hyungjin Chung, Jong Chul Ye, Marc Louis Klasky

Proceedings of the IEEE International Conference on Image Processing, 2023

Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models.

Suhyeon Lee, Hyungjin Chung, Minyoung Park, Jonghyuk Park, Wi-Sun Ryu, Jong Chul Ye

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Solving 3D Inverse Problems Using Pre-Trained 2D Diffusion Models.

Hyungjin Chung, Dohoon Ryu, Michael T. McCann, Marc Louis Klasky, Jong Chul Ye

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Parallel Diffusion Models of Operator and Image for Blind Inverse Problems.

Hyungjin Chung, Jeongsol Kim, Sehui Kim, Jong Chul Ye

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement: An overview from a signal processing perspective.

Mehmet Akçakaya, Burhaneddin Yaman, Hyungjin Chung, Jong Chul Ye

IEEE Signal Process. Mag., 2022

Score-based diffusion models for accelerated MRI.

Hyungjin Chung, Jong Chul Ye

Medical Image Anal., 2022

Progressive Deblurring of Diffusion Models for Coarse-to-Fine Image Synthesis.

Sangyun Lee, Hyungjin Chung, Jaehyeon Kim, Jong Chul Ye

CoRR, 2022

Improving Diffusion Models for Inverse Problems using Manifold Constraints.

Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction.

Hyungjin Chung, Byeongsu Sim, Jong Chul Ye

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution.

Eunju Cha, Hyungjin Chung, Eung-Yeop Kim, Jong Chul Ye

IEEE Trans. Medical Imaging, 2021

Missing Cone Artifact Removal in ODT Using Unsupervised Deep Learning in the Projection Domain.

Hyungjin Chung, Jaeyoung Huh, Geon Kim, YongKeun Park, Jong Chul Ye

IEEE Trans. Computational Imaging, 2021

Deep learning STEM-EDX tomography of nanocrystals.

Yoseob Han, Jaeduck Jang, Eunju Cha, Junho Lee, Hyungjin Chung, Myoungho Jeong, Tae-Gon Kim, Byeong Gyu Chae, Hee Goo Kim, Shinae Jun, Sungwoo Hwang, Eunha Lee, Jong Chul Ye

Nat. Mach. Intell., 2021

Reusability report: Feature disentanglement in generating a three-dimensional structure from a two-dimensional slice with sliceGAN.

Hyungjin Chung, Jong Chul Ye

Nat. Mach. Intell., 2021

Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data.

Hyungjin Chung, Eunju Cha, Leonard Sunwoo, Jong Chul Ye

Medical Image Anal., 2021

Unsupervised Deep Learning Methods for Biological Image Reconstruction.

Mehmet Akçakaya, Burhaneddin Yaman, Hyungjin Chung, Jong Chul Ye

CoRR, 2021

Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning.

Hyungjin Chung, Jaehyun Kim, Jeong Hee Yoon, Jeong Min Lee, Jong Chul Ye

CoRR, 2021

Feature Disentanglement in generating three-dimensional structure from two-dimensional slice with sliceGAN.

Hyungjin Chung, Jong Chul Ye

CoRR, 2021

Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography.

Hyungjin Chung, Jaeyoung Huh, Geon Kim, YongKeun Park, Jong Chul Ye

CoRR, 2021

2020

Unpaired Deep Learning for Accelerated MRI Using Optimal Transport Driven CycleGAN.

Gyutaek Oh, Byeongsu Sim, Hyungjin Chung, Leonard Sunwoo, Jong Chul Ye

IEEE Trans. Computational Imaging, 2020

Unsupervised Deep Learning for MR Angiography with Flexible Temporal Resolution.

Eunju Cha, Hyungjin Chung, Eung-Yeop Kim, Jong Chul Ye

CoRR, 2020

Deep Learning Fast MRI Using Channel Attention in Magnitude Domain.

Joonhyung Lee, Hyunjong Kim, Hyungjin Chung, Jong Chul Ye

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020