14 citations · 27 across the 4 of their papers we have counts for
4 papers
Revisiting Misalignment in Multispectral Pedestrian Detection: A Language-Driven Approach for Cross-modal Alignment Fusion
Taeheon Kim, Sangyun Chung, Youngjoon Yu +1
Multispectral pedestrian detection is a crucial component in various critical applications. However, a significant challenge arises due to the misalignment between these modalities…
Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection
Taeheon Kim, Sebin Shin, Youngjoon Yu +2
RGBT multispectral pedestrian detection has emerged as a promising solution for safety-critical applications that require day/night operations. However, the modality bias problem r…
MSCoTDet: Language-driven Multi-modal Fusion for Improved Multispectral Pedestrian Detection
Taeheon Kim, Sangyun Chung, Damin Yeom +3
Multispectral pedestrian detection is attractive for around-the-clock applications due to the complementary information between RGB and thermal modalities. However, current models…
VisAR: Bringing Interactivity to Static Data Visualizations through Augmented Reality
Taeheon Kim, Bahador Saket, Alex Endert +1
Static visualizations have analytic and expressive value. However, many interactive tasks cannot be completed using static visualizations. As datasets grow in size and complexity,…