Seongyong Ahn — accepted AI-conference papers

2024

METAVerse: Meta-Learning Traversability Cost Map for Off-Road Navigation

Junwon Seo, Taekyung Kim, Seongyong Ahn, Kiho Kwak

IROS 2024

Autonomous navigation in off-road conditions requires an accurate estimation of terrain traversability. However, traversability estimation in unstructured environments is subject to high uncertainty due to the variability of numerous factors that influence vehicle-terrain interaction. Consequently,

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2022

SLiDE: Self-Supervised LiDAR De-Snowing through Reconstruction Difficulty

Gwangtak Bae, Byungjun Kim, Seongyong Ahn, Jihong Min, Inwook Shim

ECCV 2022poster

"LiDAR is widely used to capture accurate 3D outdoor scene structures. However, LiDAR produces many undesirable noise points in snowy weather, which hamper analyzing meaningful 3D scene structures. Semantic segmentation with snow labels would be a straightforward solution for removing them, but it r…

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