4 papers
Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution
Junseo Bang, Joonhee Lee, Kyeonghyun Lee +3
Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-scale super-resolution. Recent approac…
Physics-Guided Deep Learning For High Resolution X-ray Imaging
Shao Xian Lee, Aashwin Ananda Mishra, Ariel Arnott +21
Imperfections in X-ray imaging systems can limit their performance, especially in High Energy Density (HED) or Inertial Fusion Energy (IFE)-relevant experiments that are typically…
A Target-Free Harmonization Method for MRI
Minjun Kim, Dong Ju Mun, Hwihun Jeong +4
In MRI, variations in scan parameters, sequence, or hardware can lead to discrepancies in image appearance, even for the same subject. These inconsistencies, known as domain shifts…
Geometrical Properties of Text Token Embeddings for Strong Semantic Binding in Text-to-Image Generation
Hoigi Seo, Junseo Bang, Haechang Lee +3
Text-to-image (T2I) models often suffer from text-image misalignment in complex scenes involving multiple objects and attributes. Semantic binding has attempted to associate the ge…