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
07.2023 | I gave an invited talk, titled Towards Robust Shape Correspondence: Learning with Receptive Field Optimization, in the Group of Geometric Computation and Visualisation led by Prof. Shengjun Liu at Central South University, China. |
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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. |
more... |
Selected Publications
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CVPR
Generalizable Local Feature Pre-training for Deformable Shape AnalysisIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 -
NeurIPS
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape MatchingIn Neural Information Processing Systems 2022 -
CG&A
Fast Sketch Segmentation and Labeling with Deep LearningIEEE Computer Graphics and Applications 2018