Kyusung Cho — accepted AI-conference papers

2024

Geometric Exploitation for Indoor Panoramic Semantic Segmentation

Duc Cao Dinh, Seok Joon Kim, Kyusung Cho

NeurIPS 2024poster

PAnoramic Semantic Segmentation (PASS) is an important task in computer vision, as it enables semantic understanding of a 360° environment. Currently, most of existing works have focused on addressing the distortion issues in 2D panoramic images without considering spatial properties of indoor scene…

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2023

Fast and Versatile Feature-Based LiDAR Odometry via Efficient Local Quadratic Surface Approximation

Seungwon Choi, Hee-Won Chae, Yunsuk Jeung, Seokjoon Kim, Kyusung Cho, Tae-wan Kim

RA-L 2023

We present a fast and versatile feature-based LiDAR odometry method using local quadratic surface approximation and point-to-surface alignment. Unlike most feature-based methods, our approach approximates the local geometry of the LiDAR scan as a quadratic surface to mitigate performance degradation

Cited by 13 Source ↗Scholar ↗