Lei LI

3D AI Lab, Technical University of Munich, Germany

Lei Li is a postdoctoral researcher working with Prof. Angela Dai at the 3D AI Lab, Technical University of Munich, Germany. Previously, he worked as a postdoctoral researcher with Prof. Maks Ovsjanikov from 2020 to 2022 at LIX, École Polytechnique / Inria, France. Lei earned his Ph.D. degree in computer science and engineering (2020) from The Hong Kong University of Science and Technology, and his B.Eng. degree in software engineering (2014) from Shandong University, China. He was a research intern at Alibaba A.I. Labs (2018) and Megvii Research (2019). His Ph.D. thesis advisor is Prof. Chiew-Lan Tai, and he also works closely with Prof. Hongbo Fu. Lei’s research interests lie in Computer Graphics and Computer Vision, with a focus on geometric deep learning for shape analysis.

News

03.2023 Postdoc at 3D AI Lab, Technical University of Munich.
02.2023 Our work Generalizable Local Feature Pre-training for Deformable Shape Analysis has been accepted by CVPR 2023 and selected as a highlight (10% of accepted papers, 2.5% of submissions).
01.2023 I gave an invited talk, titled Towards Robust Geometric Deep Learning for Shape Correspondence, as part of the Dell Technical Generations Series Talk organized by Dell Technologies, Shanghai.
09.2022 Our work Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching has been accepted by NeurIPS 2022.
08.2022 Our work SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence has been accepted by 3DV 2022.
more...

Selected Publications

  1. CVPR
    Generalizable Local Feature Pre-training for Deformable Shape Analysis
    Souhaib Attaiki,  Lei Li, and Maks Ovsjanikov
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023
  2. NeurIPS
    Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching
    Lei Li, Nicolas Donati, and Maks Ovsjanikov
    In Neural Information Processing Systems 2022
  3. TVCG
    WSDesc: Weakly Supervised 3D Local Descriptor Learning for Point Cloud Registration
    Lei Li, Hongbo Fu, and Maks Ovsjanikov
    IEEE Transactions on Visualization and Computer Graphics 2022
  4. CVPR
    PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
    Xuyang Bai, Zixin Luo, Lei Zhou, Hongkai Chen,  Lei Li, Zeyu Hu, Hongbo Fu, and Chiew-Lan Tai
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021
  5. CVPR
    End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
    Lei Li, Siyu Zhu, Hongbo Fu, Ping Tan, and Chiew-Lan Tai
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020
  6. TVCG
    Sketch-R2CNN: An RNN-Rasterization-CNN Architecture for Vector Sketch Recognition
    Lei Li, Changqing Zou, Youyi Zheng, Qingkun Su, Hongbo Fu, and Chiew-Lan Tai
    IEEE Transactions on Visualization and Computer Graphics 2020
  7. CG&A
    Fast Sketch Segmentation and Labeling with Deep Learning
    Lei Li, Hongbo Fu, and Chiew-Lan Tai
    IEEE Computer Graphics and Applications 2018