2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
SEMIR: Topology-Preserving Graph Minors for Thin-Structure Segmentation
Luke James Miller, Yugyung Lee
Thin-structure segmentation--power lines, cracks, lane markings at 1-3 pixel width--requires preserving connectivity that standard representations preclude: patching severs continu…
SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation
Luke James Miller, Yugyung Lee
Segmenting small and sparse structures in large-scale images is fundamentally constrained by voxel-level, lattice-bound computation and extreme class imbalance -- dense, full-resol…
MATEX: Multi-scale Attention and Text-guided Explainability of Medical Vision-Language Models
Muhammad Imran, Chi Lee, Yugyung Lee
We introduce MATEX (Multi-scale Attention and Text-guided Explainability), a novel framework that advances interpretability in medical vision-language models by incorporating anato…
Predicting When to Trust Vision-Language Models for Spatial Reasoning
Muhammad Imran, Yugyung Lee
Vision-Language Models (VLMs) demonstrate impressive capabilities across multimodal tasks, yet exhibit systematic spatial reasoning failures, achieving only 49% (CLIP) to 54% (BLIP…
Multi-Modal Interpretability for Enhanced Localization in Vision-Language Models
Muhammad Imran, Yugyung Lee
Recent advances in vision-language models have significantly expanded the frontiers of automated image analysis. However, applying these models in safety-critical contexts remains…