Point Encoder GAN: A deep learning model for 3D point cloud inpainting

被引：0
|
作者：
Yu, Yikuan [1 ,2 ]
Huang, Zitian [1 ,2 ]
Li, Fei [3 ,4 ]
Zhang, Haodong [1 ,2 ]
Le, Xinyi [1 ,2 ]
机构：
[1] School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai,20040, China
[2] Shanghai Key Laboratory of Advanced Manufacturing Environment, Shanghai,200240, China
[3] State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing,100854, China
[4] Beijing Complex Product Advanced Manufacturing Research Center, Beijing Simulation Center, Beijing,100854, China
来源：
Neurocomputing | 2020年 / 384卷
关键词：
45;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
下载
收藏
页码：192 / 199
相关论文
共 50 条
  • [21] Learning Representative Features by Deep Attention Network for 3D Point Cloud Registration
    Xia, Xiaokai
    Fan, Zhiqiang
    Xiao, Gang
    Chen, Fangyue
    Liu, Yu
    Hu, Yiheng
    SENSORS, 2023, 23 (08)
  • [22] DEEP LEARNING ON POINT CLOUD FOR 3D CLASSIFICATION BASED ON SPIKING NEURAL NETWORK
    Zhang Silin
    2022 19TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP), 2022,
  • [23] Deep Learning Based 3D Point Cloud Regression for Estimating Forest Biomass
    Oehmcke, Stefan
    Li, Lei
    Revenga, Jaime C.
    Nord-Larsen, Thomas
    Trepekli, Katerina
    Gieseke, Fabian
    Igel, Christian
    30TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS, ACM SIGSPATIAL GIS 2022, 2022, : 275 - 278
  • [24] GridNet: efficiently learning deep hierarchical representation for 3D point cloud understanding
    WANG Huiqun
    HUANG Di
    WANG Yunhong
    Frontiers of Computer Science, 2022, 16 (01)
  • [25] Research progress of 3D point cloud analysis methods based on deep learning
    Chen H.
    Wu Y.
    Zhang Y.
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2023, 44 (11): : 130 - 158
  • [26] GridNet: efficiently learning deep hierarchical representation for 3D point cloud understanding
    Wang, Huiqun
    Huang, Di
    Wang, Yunhong
    FRONTIERS OF COMPUTER SCIENCE, 2022, 16 (01)
  • [27] Deep learning with simulated laser scanning data for 3D point cloud classification
    Esmoris, Alberto M.
    Weiser, Hannah
    Winiwarter, Lukas
    Cabaleiro, Jose C.
    Hofle, Bernhard
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2024, 215 : 192 - 213
  • [28] GridNet: efficiently learning deep hierarchical representation for 3D point cloud understanding
    Huiqun Wang
    Di Huang
    Yunhong Wang
    Frontiers of Computer Science, 2022, 16
  • [29] Inception-based Deep Learning Architecture for 3D Point Cloud Completion
    Saffi, Houda
    Hmamouche, Youssef
    Elharrouss, Omar
    Seghrouchni, Amal El Fallah
    2022 18TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (AVSS 2022), 2022,
  • [30] CLOSED: A Dashboard for 3D Point Cloud Segmentation Analysis using Deep Learning
    Zoumpekas, Thanasis
    Molina, Guillem
    Puig, Anna
    Salamo, Maria
    PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 4, 2022, : 403 - 410
12345