1 citations · 1 across the 6 of their papers we have counts for
7 papers
MaDeL: Manifold-Decomposed Feature Losses for Generative Modeling
Beomsu Kim, Jong Chul Ye, Kwanyoung Kim
Generative models are often trained with isotropic objectives such as mean-squared error. For data concentrated near a low-dimensional manifold, however, such losses conflate displ…
UNICORN: Ultrasound Nakagami Imaging via Score Matching and Adaptation for Assessing Hepatic Steatosis
Kwanyoung Kim, Jaa-Yeon Lee, Youngjun Ko +2
Ultrasound imaging is an essential first-line tool for assessing hepatic steatosis. While conventional B-mode ultrasound imaging has limitations in providing detailed tissue charac…
CrimEdit: Controllable Editing for Counterfactual Object Removal, Insertion, and Movement
Boseong Jeon, Junghyuk Lee, Jimin Park +4
Recent works on object removal and insertion have enhanced their performance by handling object effects such as shadows and reflections, using diffusion models trained on counterfa…
Single-Step Bidirectional Unpaired Image Translation Using Implicit Bridge Consistency Distillation
Suhyeon Lee, Kwanyoung Kim, Jong Chul Ye
Unpaired image-to-image translation has seen significant progress since the introduction of CycleGAN. However, methods based on diffusion models or Schrödinger bridges have yet to…
UNICORN: Ultrasound Nakagami Imaging via Score Matching and Adaptation
Kwanyoung Kim, Jaa-Yeon Lee, Jong Chul Ye
Nakagami imaging holds promise for visualizing and quantifying tissue scattering in ultrasound waves, with potential applications in tumor diagnosis and fat fraction estimation whi…
OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation
Kwanyoung Kim, Yujin Oh, Jong Chul Ye
The recent success of CLIP has demonstrated promising results in zero-shot semantic segmentation by transferring muiltimodal knowledge to pixel-level classification. However, lever…
End-to-End Breast Cancer Radiotherapy Planning via LMMs with Consistency Embedding
Kwanyoung Kim, Yujin Oh, Sangjoon Park +5
Recent advances in AI foundation models have significant potential for lightening the clinical workload by mimicking the comprehensive and multi-faceted approaches used by medical…