OpenPointCloud: An Open-Source Algorithm Library of Deep Learning Based Point Cloud Compression

被引:3
|
作者
Gao, Wei [1 ,2 ]
Ye, Hua [2 ]
Li, Ge [1 ]
Zheng, Huiming [1 ,2 ]
Wu, Yuyang [1 ,2 ]
Xie, Liang [1 ,2 ]
机构
[1] Peking Univ, Sch Elect & Comp Engn, Shenzhen Grad Sch, Shenzhen, Peoples R China
[2] Peng Cheng Lab, Inst Open Sources, Shenzhen, Peoples R China
基金
国家重点研发计划;
关键词
Point Cloud; Geometry Compression; Open-source Software; Algorithm Library; Deep Learning;
D O I
10.1145/3503161.3548545
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper gives an overview of OpenPointCloud, the first open-source algorithm library containing outstanding deep learning methods on point cloud compression (PCC). We provide an introduction of our implementations, including 8 methods on lossless geometry PCC and lossy geometry PCC. Principles and contributions of these methods in our algorithm library are illustrated, which are also implemented with different deep learning programming frameworks, such as TensorFlow, Pytorch and TensorLayer. In order to systematically evaluate the performances of all these methods, we conduct a comprehensive benchmarking test. We provide analyses and comparisons of their performances according to their categories and draw constructive conclusions. This algorithm library has been released at https://git.openi.org.cn/OpenPointCloud.
引用
收藏
页码:7347 / 7350
页数:4
相关论文
共 50 条
  • [31] Guest editorial: Deep learning-based point cloud processing, compression and analysis
    Zhang, Yun
    Hamzaoui, Raouf
    Wang, Xu
    Hou, Junhui
    Valenzise, Giuseppe
    [J]. ELECTRONICS LETTERS, 2024, 60 (14)
  • [32] A Deep Learning-Based Algorithm for Predicting the Turning Point of Cloud Workload
    Jain, Anmol
    Panda, Sanjaya Kumar
    [J]. IFIP Advances in Information and Communication Technology, 723 IFIP : 276 - 287
  • [33] Algorithm for point cloud compression based on geometrical features
    Qiao S.
    Zhang K.
    Gao K.
    [J]. International Journal of Performability Engineering, 2019, 15 (03) : 782 - 791
  • [34] Implementing Deep Learning Algorithms in Anatomic Pathology Using Open-source Deep Learning Libraries
    McAlpine, Ewen
    Michelow, Pamela
    [J]. ADVANCES IN ANATOMIC PATHOLOGY, 2020, 27 (04) : 260 - 268
  • [35] A Novel Point Cloud Compression Algorithm Based on Clustering
    Sun, Xuebin
    Ma, Han
    Sun, Yuxiang
    Liu, Ming
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2019, 4 (02) : 2132 - 2139
  • [36] Development and Validation of a Deep Learning Algorithm and Open-Source Platform for the Automatic Labelling of Motion Capture Markers
    Clouthier, Allison L.
    Ross, Gwyneth B.
    Mavor, Matthew P.
    Coll, Isabel
    Boyle, Alistair
    Graham, Ryan B.
    [J]. IEEE ACCESS, 2021, 9 : 36444 - 36454
  • [37] An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography
    Burke, Jamie
    Engelmann, Justin
    Hamid, Charlene
    Reid-Schachter, Megan
    Pearson, Tom
    Pugh, Dan
    Dhaun, Neeraj
    Storkey, Amos
    King, Stuart
    Macgillivray, Tom J.
    Bernabeu, Miguel O.
    Maccormick, Ian J. C.
    [J]. TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 2023, 12 (11):
  • [38] oneAPI Open-Source Math Library Interface
    Krainiuk, Mariia
    Goli, Mehdi
    Pascuzzi, Vincent R.
    [J]. PROCEEDINGS OF 2021 INTERNATIONAL WORKSHOP ON PERFORMANCE, PORTABILITY & PRODUCTIVITY IN HPC (P3HPC 2021), 2021, : 22 - 32
  • [39] Open-source library of tissue engineering scaffolds
    Martinez Cendrero, Adrian
    Franco Martinez, Francisco
    Solorzano Requejo, William Gabriel
    Diaz Lantada, Andres
    [J]. MATERIALS & DESIGN, 2022, 223
  • [40] Open-source, machine and deep learning-based automated algorithm for gestational age estimation through smartphone lens imaging
    Desai, Arjun D.
    Peng, Chunlei
    Fang, Leyuan
    Mukherjee, Dibyendu
    Yeung, Andrew
    Jaffe, Stephanie J.
    Griffin, Jennifer B.
    Farsiu, Sina
    [J]. BIOMEDICAL OPTICS EXPRESS, 2018, 9 (12): : 6038 - 6052