6 papers
A Sparse Topometric Graph for Scalable Cross-Session Indoor Navigation
Eun Sun Lee, Minkyun Seo, Gwangtak Bae +4
A conventional embodied agent in an indoor environment builds a map by accumulating noisy real-world measurements and results from heavy inference to guide navigation. While the de…
RoEL: Robust Event-based 3D Line Reconstruction
Gwangtak Bae, Jaeho Shin, Seunggu Kang +3
Event cameras in motion tend to detect object boundaries or texture edges, which produce lines of brightness changes, especially in man-made environments. While lines can constitut…
Finding 3D Scene Analogies with Multimodal Foundation Models
Junho Kim, Young Min Kim
Connecting current observations with prior experiences helps robots adapt and plan in new, unseen 3D environments. Recently, 3D scene analogies have been proposed to connect two 3D…
Learning 3D Scene Analogies with Neural Contextual Scene Maps
Junho Kim, Gwangtak Bae, Eun Sun Lee +1
Understanding scene contexts is crucial for machines to perform tasks and adapt prior knowledge in unseen or noisy 3D environments. As data-driven learning is intractable to compre…
Fully Geometric Panoramic Localization
Junho Kim, Jiwon Jeong, Young Min Kim
We introduce a lightweight and accurate localization method that only utilizes the geometry of 2D-3D lines. Given a pre-captured 3D map, our approach localizes a panorama image, ta…
Self-Supervised Domain Adaptation for Visual Navigation with Global Map Consistency
Eun Sun Lee, Junho Kim, Young Min Kim
We propose a light-weight, self-supervised adaptation for a visual navigation agent to generalize to unseen environment. Given an embodied agent trained in a noiseless environment,…