28 citations · 70 across the 14 of their papers we have counts for
8 papers · 1 filter
Rethinking 3D Segmentation from Individual LiDAR Scans: Incidence-Aware Sampling on the SIP Benchmark
Seongyong Kim, Jingdao Chen, Yong Kwon Cho
3D scene understanding is increasingly important in construction, yet most methods are developed on curated datasets that do not fully reflect real site sensing conditions. In many…
X-DECODE: EXtreme Deblurring with Curriculum Optimization and Domain Equalization
Sushant Gautam, Jingdao Chen
Restoring severely blurred images remains a significant challenge in computer vision, impacting applications in autonomous driving, medical imaging, and photography. This paper int…
Analysis of LiDAR Configurations on Off-road Semantic Segmentation Performance
Jinhee Yu, Jingdao Chen, Lalitha Dabbiru +1
This paper investigates the impact of LiDAR configuration shifts on the performance of 3D LiDAR point cloud semantic segmentation models, a topic not extensively studied before. We…
A Hybrid Semantic-Geometric Approach for Clutter-Resistant Floorplan Generation from Building Point Clouds
Seongyong Kim, Yosuke Yajima, Jisoo Park +2
Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial r…
Improving Contrastive Learning on Visually Homogeneous Mars Rover Images
Isaac Ronald Ward, Charles Moore, Kai Pak +2
Contrastive learning has recently demonstrated superior performance to supervised learning, despite requiring no training labels. We explore how contrastive learning can be applied…
Mixed-domain Training Improves Multi-Mission Terrain Segmentation
Grace Vincent, Alice Yepremyan, Jingdao Chen +1
Planetary rover missions must utilize machine learning-based perception to continue extra-terrestrial exploration with little to no human presence. Martian terrain segmentation has…