Jaeho Shin

Papers

Total Citations

H-Index

About

Jaeho Shin is a leading researcher in computer vision and robotics, with a primary focus on transparent object perception and multispectral sensing. His most impactful work, the TRansPose dataset (2023, 11 citations), addresses a fundamental challenge in the field: conventional RGB and depth cameras struggle to detect transparent objects due to their unique optical properties. By introducing a large-scale multispectral dataset that leverages thermal infrared cameras, Shin demonstrated how long-wave infrared imaging can overcome these limitations, enabling more reliable recognition of glass, plastic, and other see-through materials. This contribution is critical for applications in autonomous manipulation, warehouse logistics, and assistive robotics, where transparent objects are ubiquitous yet notoriously difficult to perceive. Shin’s research bridges the gap between thermal sensing and deep learning, providing a benchmark that has already influenced subsequent work in material-agnostic vision systems. His achievements highlight the untapped potential of non-visible spectra for robust perception, positioning him as an innovator in multispectral computer vision.