MP-P.PZ4: Point Cloud Processing
Mon, 17 Oct, 22:00 - 00:30 China Standard Time (UTC +8)
Mon, 17 Oct, 16:00 - 18:30 Central European Time (UTC +1)
Mon, 17 Oct, 14:00 - 16:30 UTC
Mon, 17 Oct, 10:00 - 12:30 Eastern Time (UTC -5)
Poster
Location: Poster Zone 4
Session Co-Chairs: Jean-Christophe Pesquet, CentraleSupélec and Andrea Cavallaro, Queen Mary University of London and Rebecca Willett, University of Chicago
Track: Three-Dimensional Image and Video Processing

MP-P.PZ4.1: Unsupervised Point Cloud Pre-training via Contrasting and Clustering
Guofeng Mei, Jian Zhang, Qiang Wu, University of Technology Sydney, Australia; Xiaoshui Huang, Shanghai AI Laboratory, China; Juan Liu, Beijing Institute of Technology, China

MP-P.PZ4.2: 3D-SELFCUTMIX: SELF-SUPERVISED LEARNING FOR 3D POINT CLOUD ANALYSIS
Yuan-Yi Xu, Yan-Yang Ji, Sheng-Yu Huang, Zhi-Hao Lin, Yu-Chiang Frank Wang, National Taiwan University, Taiwan

MP-P.PZ4.3: Partial Point Cloud Registration via Soft Segmentation
Guofeng Mei, Jian Zhang, Qiang Wu, University of Technology Sydney, Australia; Xiaoshui Huang, Shanghai AI Laboratory, China

MP-P.PZ4.4: DEEP LEARNING CLASSIFICATION OF LARGE-SCALE POINT CLOUDS: A CASE STUDY ON CUNEIFORM TABLETS
Frederik Hagelskjaer, University of Southern Denmark, Denmark

MP-P.PZ4.5: FREQUENCY-SELECTIVE GEOMETRY UPSAMPLING OF POINT CLOUDS
Viktoria Heimann, Andreas Spruck, André Kaup, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

MP-P.PZ4.6: SUBJECTIVE QUALITY EVALUATION OF POINT CLOUDS WITH 3D STEREOSCOPIC VISUALIZATION
Joao Prazeres, Manuela Pereira, Antonio Pinheiro, Instituto de Telecomunicacoes and Universidade da Beira Interior, Portugal

MP-P.PZ4.7: NON-RIGID MULTIPLE POINT SET REGISTRATION USING LATENT GAUSSIAN MIXTURE
Hao Huang, Cheng Chen, New York University, United States of America; Yi Fang, New York University Abu Dhabi, United Arab Emirates

MP-P.PZ4.8: BLIND QUALITY OF A 3D RECONSTRUCTED MESH
Rémy Alcouffe, Simone Gasparini, Géraldine Morin, Sylvie Chambon, University of Toulouse, IRIT - Toulouse INP, France

MP-P.PZ4.9: Learning-based Lossless Point Cloud Geometry Coding using Sparse Tensors
Dat Thanh Nguyen, André Kaup, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany