Jianqiang Wang（王剑强）

I am a Ph.D student at Nanjing University, where I am advised by Prof. Zhan Ma. I received the B.S. and M.S. degrees in electronic science and engineering from Nanjing University, in 2018 and 2021. My research interests include image processing and computer vision. I am actively looking for a full-time research job in 2024, Feel free to contact me if you are interested in.

Email: wangjq@smail.nju.edu.cn   /   WeChat ID: yydlmzyz

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Research

My main interest lies in visual data compression, including:

  • Learning-based Data Compression
  • 3D Data (Point Cloud) Compression
Education
Nanjing University, Nanjing, China
Ph.D. in Information and Communication Engineering
Sept. 2021 - Dec. 2024 (Expected)
Advisor: Zhan Ma and Dandan Ding
Nanjing University, Nanjing, China
M.E. in Electronics and Communication Engineering
Sept. 2018 - Jun. 2021
Advisor: Zhan Ma
Nanjing University, Nanjing, China
B.S. in Electronic Information Science and Technology
Sept. 2014 - Jun. 2018
Internship
OPPO, Nanjing, China
Video Coding Researcher (on Learning-based point cloud attribute compression)
Dec. 2022 - July 2023
Advisor: Dong Wang
Aliyun (Alibaba Cloud), Hangzhou, China
Video Coding Engineer (on LiDAR point cloud compression)
Jun. 2020 - Sept. 2020
Advisor: Ying Chen
Shanghai Jiao Tong University, Shanghai, China
Visiting Student (on Learning-based point cloud geometry compression)
Jun. 2019 - Sept. 2019
Advisor: Yiling Xu
Duke Kunshan University, Suzhou, China
Assistant Engineer (on Raw image compression)
May 2018 - Sept. 2018
Advisor: David Brady and Xuefei Yan
Selected Publications

2024
    A Versatile Point Cloud Compressor Using Universal Multiscale Conditional Coding -- Part I: Geometry
    Jianqiang Wang#, Ruixiang Xue#, Jiaxin Li, Dandan Ding, Yi Lin, Zhan Ma* (# - equal contribution; * - corresponding author.)
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.   (SCI JCR Q1, IF=20.8; CCF A)
    A Versatile Point Cloud Compressor Using Universal Multiscale Conditional Coding -- Part II: Attribute
    Jianqiang Wang, Ruixiang Xue, Jiaxin Li, Dandan Ding, Yi Lin, Zhan Ma*
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.   (SCI JCR Q1, IF=20.8; CCF A)

    A Versatile Multiscale Conditional Coding framework, Unicorn, is proposed to compress the geometry and attribute of any given point cloud. Attribute compression is discussed in Part II of this paper, while geometry compression is given in Part I of this paper.

    2023
      Lossless Point Cloud Attribute Compression Using Cross-scale, Cross-group, and Cross-color Prediction
      Jianqiang Wang, Dandan Ding, Zhu Li, Zhan Ma*
      2023 Data Compression Conference (DCC), 2023.   (CCF B)

      This work extends the multiscale structure originally developed for point cloud geometry compression to point cloud attribute compression.

      2022
        Sparse Tensor-Based Multiscale Representation for Point Cloud Geometry Compression
        Jianqiang Wang, Dandan Ding, Zhu Li, Xiaoxing Feng, Chuntong Cao, Zhan Ma*
        IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.   (SCI JCR Q1, IF=20.8; CCF A)
        code

        A unified Point Cloud Geometry (PCG) compression method through the processing of multiscale sparse tensor-based voxelized point cloud.
        Sparse Tensor-based Point Cloud Attribute Compression
        Jianqiang Wang, Zhan Ma*
        2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), 2022.

        This work is probably the first attempt to extend sparse convolutions for point cloud attribute compression.

        2021
        Multiscale Point Cloud Geometry Compression
        Jianqiang Wang, Dandan Ding, Zhan Ma*
        2021 Data Compression Conference (DCC), 2021.   (CCF B)
        code / video

        We propose a multiscale end-to-end learning framework that hierarchically reconstructs the 3D Point Cloud Geometry (PCG) via progressive re-sampling, which is developed on top of a sparse convolution based autoencoder.

        2020
        Lossy Point Cloud Geometry Compression via End-to-End Learning
        Jianqiang Wang, Hao Zhu, Haojie Liu, Zhan Ma*
        IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2021.   (SCI JCR Q1, IF=8.4; CCF B)   (2023 IEEE CAS Society Outstanding Young Author Award)
        code / video

        A novel end-to-end Learned Point Cloud Geometry Compression framework.
        Standard Contributions and Patents
      • J. Wang, R. Xue, J. Li, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC][EE5.4-Related] Update On the Training Datasets for Attribute Compression", MPEG m64417, July 2023.
      • J. Wang, R. Xue, J. Li, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC] On the Training Datasets for Attribute Compression", MPEG m62176, Jan. 2023.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, and D. Wang, [AI-3DGC][EE5.3-Related] Dynamic SparsePCGC Update", MPEG m61006, Oct. 2022.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, and D. Wang, "[AI-3DGC] Lossless SparsePCAC: Multiscale Sparse Representation for Lossless Point Cloud Attribute Compression", MPEG m61007, Oct. 2022.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC][EE13.54-related] SparsePCGCv1 Update: Improvements on Dense/Sparse/LiDAR Point Clouds", MPEG m60352, July 2022.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC][EE13.54-related] SparsePCGCv3: Dynamic SparsePCGC with Inter Frame Prediction", MPEG m60354, July 2022.
      • J. Wang, R. Xue, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC] [EE13.54-related] SparsePCGCv2: Improved SparsePCGC with attention mechanism", MPEG m59552, April 2022.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC][EE13.54-Related] Point Cloud Geometry Compression Using Sparse Tensor-based Multiscale Representation", MPEG m59035, Jan. 2022.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC] Point Cloud Attribute Compression Using Sparse Tensor Representation", MPEG m59037, Jan. 2022.
      • J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "A Geometry Compression Framework for AI-based PCC via Sparse Convolution," Online: MPEG m57453, Jul 2021.
      • R. Xue, J. Wang, J. Li, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC] [EE5.1-related] [EE5.3- related] Dynamic Point Cloud Geometry Compression for LiDAR Point Cloud with Ego-Motion Compensation", MPEG m62177, Jan. 2023
      • R. Xue, J. Wang, Z. Ma, H. Wei, Y. Yu, V. Zakharchenko, D. Wang, "[AI-3DGC][EE13.54-related] SparsePCGCv2: Multihead Neighborhood Point Attention for Sparse Point Clouds", MPEG m60353, July 2022.
        • Honors and Awards
      • 2023 IEEE CAS Society Outstanding Young Author Award.
      • 2023 Huawei Scholarship, Nanjing University.
      • 2019 The Second Prize of the 16th China Post-Graduate Mathematical Contest in Modeling
        • Academic Services
        Reviewer for TPAMI, TIP, TCSVT, TMM, TOMM, JETCAS, ICME, ICRA, ICIP, etc.


        Template credit to Jon Barron