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
Session:
TH1.R10: Scalable and Efficient Processing of Large-Scale LiDAR Point Clouds Oral
Track:
Community Contributed Themes
Location:
TBD
Presentation Time:
Thu, 13 Aug, 09:00 - 09:15
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
Contacts