Ziyi Wang

I am a fourth year PhD student in the Department of Automation at Tsinghua University, advised by Prof. Jiwen Lu . In 2020, I obtained my B.Eng. in the Department of Electronic Engineering, Tsinghua University. I also obtained B.Admin. as dual degree in the School of Ecnomics and Management, Tsinghua University.

I am broadly interested in computer vision and deep learning. My current research focuses on 3D vision.

Email  /  Google Scholar  /  Github

profile photo

  • 2023-07: 1 paper on 3D generative pre-training is accepted to ICCV 2023.
  • 2023-07: The journal paper of PV-RAFT is accepted to TPAMI 2023.
  • 2022-09: 1 paper (spotlight) on 3D prompt learning is accepted to NeurIPS 2022.
  • 2022-03: 1 paper on 3D semantic segmentation is accepted to CVPR 2022.
  • 2021-07: 2 papers (including 1 oral) are accepted to ICCV 2021.
  • 2021-03: 1 paper on 3D scene flow estimation is accepted to CVPR 2021.
  • Publications

    * indicates equal contribution

    dise 3D Point-Voxel Correlation Fields for Scene Flow Estimation
    Ziyi Wang*, Yi Wei*, Yongming Rao, Jie Zhou , Jiwen Lu
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
    [IEEE] [Code] [Project Page]

    DPV-RAFT is the extended journal version of PV-RAFT. We further propose Spatial Deformation and Temporal Deformation to enhance PV-RAFT.

    dise Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models
    Ziyi Wang*, Xumin Yu*, Yongming Rao, Jie Zhou , Jiwen Lu
    IEEE International Conference on Computer Vision (ICCV), 2023
    [arXiv] [Code] [Project Page]

    TAP is a 3D-to-2D generative pre-training method that generate projected images of point clouds from instructed perspectives.

    dise P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting
    Ziyi Wang*, Xumin Yu*, Yongming Rao*, Jie Zhou , Jiwen Lu
    Conference on Neural Information Processing Systems (NeurIPS), 2022
    [arXiv] [Code] [Project Page] [中文解读]

    P2P is a framework to leverage large-scale pre-trained image models for 3D point cloud analysis.

    dise SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation
    Ziyi Wang, Yongming Rao, Xumin Yu, Jie Zhou , Jiwen Lu
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    [arXiv] [Code]

    We present Semantic-Affine Transformation that transforms decoder mid-level features of the encoder-decoder segmentation network with class-specific affine parameters.

    dise PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
    Xumin Yu*, Yongming Rao*, Ziyi Wang, Zuyan Liu, Jiwen Lu , Jie Zhou
    IEEE International Conference on Computer Vision (ICCV), 2021
    Oral Presentation
    [arXiv] [Code] [中文解读]

    PoinTr is a transformer-based framework that reformulates point cloud completion as a set-to-set translation problem.

    dise Towards Interpretable Deep Metric Learning with Structural Matching
    Wenliang Zhao*, Yongming Rao*, Zyi Wang, Jiwen Lu , Jie Zhou
    IEEE International Conference on Computer Vision (ICCV), 2021
    [arXiv] [Code]

    We present a deep interpretable metric learning (DIML) that adopts a structural matching strategy to explicitly aligns the spatial embeddings by computing an optimal matching flow between feature maps of the two images.

    dise PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds
    Yi Wei *, Ziyi Wang*, Yongming Rao*, Jiwen Lu , Jie Zhou
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
    [arXiv] [Code]

    We present point-voxel correlation fields for 3D scene flow estimation which migrates the high performance of RAFT and provides a solution to build structured all-pairs correlation fields for unstructured point clouds.

    Honors and Awards

  • 2023 CVPR Outstanding Reviewer
  • 2021 Haining Talent Scholarship, Tsinghua University
  • 2020 Excellent graduation thesis, Tsinghua University
  • 2018 Zheng Geru Scholarship, Tsinghua University
  • 2017 Hongqian Electronics Scholarship, Tsinghua University

  • Website Template

    © Ziyi Wang | Last updated: Jul 28, 2023