TH1.R10.2
LEARNING-BASED 3D RECONSTRUCTION OF POWER NETWORKS FROM AERIAL POINT CLOUDS
Rishabh Jain, Anuja Saini, Vishal Jain, AIDASH, India
Session:
TH1.R10: Scalable and Efficient Processing of Large-Scale LiDAR Point Clouds Oral
Track:
Community Contributed Themes
Location:
Gunston
Presentation Time:
Thursday, 13 August, 08:45 - 09:00
Session Co-Chairs:
Jonathan Li, university of waterloo and Dening Lu,
Presentation
Discussion
Resources
No resources available.
Session TH1.R10
TH1.R10.1: GEOSPATIAL TRANSFER LEARNING FOR ALS 3D LIDAR POINT CLOUDS
Shreelakshmi C R, Surya S Durbha, Indian Institute of Technology Bombay, India
TH1.R10.2: LEARNING-BASED 3D RECONSTRUCTION OF POWER NETWORKS FROM AERIAL POINT CLOUDS
Rishabh Jain, Anuja Saini, Vishal Jain, AIDASH, India
TH1.R10.3: Single-Image Point Cloud Colorization Using Deep Learning with Frequency-Domain Geometric Supervision
Hang Zhao, Jian Li, Vahidreza Gharehbaghi, Caroline Bennett, Remy D Lequesne, University of Kansas, Australia
TH1.R10.4: Point-SCT: A Multiscale Spatial Convolution-Swin Transformer Network for Point Cloud Ground Filtering in Complex Mountainous Terrains
Jingxiang Li, University of Waterloo, Canada; Fuquan Tang, Xi’an University of Science and Technology, China; Lingfei Ma, East China Normal University, China; Chao Zhu, Xi’an University of Science and Technology, China; Zheng Gong, Jimei University, China; Nur Intan Raihana Ruhaiyem, Universiti Sains Malaysia, Malaysia; Jonathan Li, University of Waterloo, Canada
TH1.R10.5: 3DLCDM: Hybrid supervision for land cover discovery mapping of emerging urban structures in 3D remote sensing
Jing Du, John Zelek, Dedong Zhang, Jonathan Li, university of waterloo, Canada
Resources
No resources available.