Lei Li
3D AI Lab, Technical University of Munich, Germany
Lei Li is currently a postdoctoral researcher at Technical University of Munich, Germany, working with Prof. Angela Dai. Previously, he worked as a postdoctoral researcher with Prof. Maks Ovsjanikov from 2020 to 2022 at LIX, École Polytechnique / Inria, France. Lei received his PhD in Computer Science and Engineering (2020) from Hong Kong University of Science and Technology, and his BEng in Software Engineering (2014) from Shandong University, China. He was a research intern at Alibaba A.I. Labs (2018) and Megvii Research (2019). His PhD thesis advisor is Prof. Chiew-Lan Tai, and he also works closely with Prof. Hongbo Fu. Lei’s research interests span computer graphics and computer vision, with a focus on neural shape analysis and human-centered computing.
News
07.2024 | Our work To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning has been accepted by ECCV 2024. |
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06.2024 | I was invited to serve as a member of the Full Papers International Program Committee of the Eurographics 2025 Conference. |
05.2024 | I gave a talk, titled Empowering Machines with Deeper Shape Understanding, at the first CS Schnupperstudium Event for Women organized by Technical University of Munich. |
02.2024 | Our work GenZI: Zero-Shot 3D Human-Scene Interaction Generation has been accepted by CVPR 2024. |
01.2024 | I was invited to serve as a member of the Technical Papers Committee of the 2024 Eurographics Symposium on Geometry Processing. |
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Selected Publications
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ECCVTo Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer LearningIn European Conference on Computer Vision 2024
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CVPRGeneralizable Local Feature Pre-training for Deformable Shape AnalysisIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023
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NeurIPSLearning Multi-resolution Functional Maps with Spectral Attention for Robust Shape MatchingIn Neural Information Processing Systems 2022
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CG&AFast Sketch Segmentation and Labeling with Deep LearningIEEE Computer Graphics and Applications 2018