8 papers · 1 filter
VLM-Aware Meta-Optic Front-End Design for Frozen Vision-Language Models
Chanik Kang, Raphaël Pestourie, Haejun Chung
Conventional machine-vision pipelines typically rely on high-quality optics that produce clean, human-interpretable images, and optical design has therefore been driven by image-le…
MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality
Yujin Park, Haejun Chung, Ikbeom Jang
Image quality in modern imaging systems emerges from the coupled effects of the sensor, optics, and computational reconstruction. Ultra-thin metalenses offer a path toward substant…
OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classification
Jiwoong Yang, Haejun Chung, Ikbeom Jang
Multi-view imaging, such as mammography and chest radiography, is a standard component of clinical practice. However, medical images are often unregistered and contain view-specifi…
CSWinUNETR: Segmentation of Thin Anatomical Structures in Medical Images
Junho Moon, Haejun Chung, Ikbeom Jang
Accurate segmentation of thin, tortuous anatomical structures, such as retinal vessels, cerebral vasculature, and facial wrinkles, remains challenging due to low contrast, frequent…
Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinations
Jiwoong Yang, Haejun Chung, Ikbeom Jang
Multi-view learning often struggles to effectively leverage images captured from diverse angles and locations. Learning methods for unstructured multi-view images remain largely un…
Dodgersort: Uncertainty-Aware VLM-Guided Human-in-the-Loop Pairwise Ranking
Yujin Park, Haejun Chung, Ikbeom Jang
Pairwise comparison labeling is emerging as it yields higher inter-rater reliability than conventional classification labeling, but exhaustive comparisons require quadratic cost. W…