32 citations · 142 across the 16 of their papers we have counts for
17 papers
Convergent Complex Quasi-Newton Proximal Methods for Gradient-Driven Denoisers in Compressed Sensing MRI Reconstruction
Tao Hong, Zhaoyi Xu, Se Young Chun +2
In compressed sensing (CS) MRI, model-based methods are pivotal to achieving accurate reconstruction. One of the main challenges in model-based methods is finding an effective prio…
Neural Diffeomorphic Non-uniform B-spline Flows
Seongmin Hong, Se Young Chun
Normalizing flows have been successfully modeling a complex probability distribution as an invertible transformation of a simple base distribution. However, there are often applica…
Rethinking Deep Image Prior for Denoising
Yeonsik Jo, Se Young Chun, Jonghyun Choi
Deep image prior (DIP) serves as a good inductive bias for diverse inverse problems. Among them, denoising is known to be particularly challenging for the DIP due to noise fitting…
Image Restoration by Deep Projected GSURE
Shady Abu-Hussein, Tom Tirer, Se Young Chun +2
Ill-posed inverse problems appear in many image processing applications, such as deblurring and super-resolution. In recent years, solutions that are based on deep Convolutional Ne…
Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring
Dongwon Park, Dong Un Kang, Se Young Chun
One of the key components for video deblurring is how to exploit neighboring frames. Recent state-of-the-art methods either used aligned adjacent frames to the center frame or prop…
Task-Aware Variational Adversarial Active Learning
Kwanyoung Kim, Dongwon Park, Kwang In Kim +1
Often, labeling large amount of data is challenging due to high labeling cost limiting the application domain of deep learning techniques. Active learning (AL) tackles this by quer…