Sunghwan (Jacob) Yoo
Sunghwan Yoo received the B.S. degree in Astrophysics and Statistics from University of Toronto, Toronto, Ontario, Canada, in 2018, and currently pursuing the Ph.D. degree in Department of Earth and Space Science and Engineering, York University, Toronto, ON, Canada. His research interests include computer vision, 3D point clouds semantic segmentation, and diffusion models.
Publications
Human vision based 3d point cloud semantic segmentation of large-scale outdoor scenes
CVPR Workshop • 2023
Fusion-SUNet: Spatial Layout Consistency for 3D Semantic Segmentation
CVPR workshop • 2023
YUTO Semantic: a Large Scale Aerial LIDAR Dataset for Semantic Segmentation
ISPRS Geospatial Week • 2023
Simulation-based data augmentation using physical priors for noise filtering deep neural network
Remote Sensing • 2020
Fusion-SUNet: Spatial Layout Consistency for 3D Semantic Segmentation
Proceedings of the Ieee/cvf Conference on Computer Vision and Pattern Recognition • 2023
Human Vision Based 3DPoint Cloud Semantic Segmentation of Large-Scale Outdoor Scenes
Ieee/cvf Conference on Computer Vision and Pattern • 2023
Yuto Semantic: a Large Scale Aerial LIDAR Dataset for Semantic Segmentation
Remote Sensing • 2023
A Unified Multi-Task Learning Framework for Dtm Generation Using Surface Differencing
Available At SSRN 5045901 • 2000
