个人简历

Xuequan Lu is a Lecturer at School of Information Technology in Deakin University,Australia. He received his Ph.D. in the College of Computer Science and Technology at Zhejiang University (China) in June 2016. His research interests include computer graphics and 3D vision. The core of his research is AI for 3D data processing/analysis, which is currently used to tackle research issues in: (1) visionbased geometry processing/analysis, (2) articulated
Research Interests
Vision-based geometry processing/analysis
e.g., mesh/point-cloud filtering, 3D reconstruction, recognition, segmentation
Articulated motion estimation/synthesis
e.g., skeleton learning, skeletal motion estimation
Physics-based animation/simulation
e.g., traffic simulation, crowd simulation, fluid simulation
Work and Education Experience
Research Fellow, Nanyang Technological University, 8/2017-present
Research Fellow, Singapore University of Technology and Design, 7/2016-7/2017
Ph.D., Computer Science, Zhejiang University (985&211: TOP 3 in China; QS World University Ranking: 68) , 9/2011-6/2016
B.S., Computer Science, Northwest A&F University (985&211: Key University in China) , 9/2007-6/2011
Honors and Awards
Outstanding Graduate Scholarship, 2016.
Outstanding Graduate, 2016.
Outstanding Doctoral Scholarship, 2015.
Outstanding Graduate Student, 2014.
Nandu Scholarship, 2013.
Outstanding Doctoral Scholarship, 2013.
Merit Graduate Student and Outstanding Graduate Student, 2013.
Second prize in National Undergraduate Mathematical Modeling, 2009.
National Encouragement Scholarship, 2009 and 2010.
Merit Student, 2008.
Nomination Prize of the Top 10 Students, 2008.
First-Class Professional Scholarship, 2008.
Key Presentation and Invited Talks
Unsupervised Articulated Skeleton Extraction from Point Set Sequences Captured by a Single Depth Camera, presented at the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Lousiana, USA, 2018
Unsupervised Articulated Skeleton Learning from Point Set Sequences Captured by a Single Depth Camera, invited talk at Technical University of Munich, Munich, Germany, 2017.
Feature-preserving Geometry Model Denoising, invited talk, University of Applied Sciences, Munich,Germany, 2017.
GMM-inspired Feature-preserving Point Set Filtering, presented at Singapore University of Technology and Design, Singapore, 2017.
A Robust Scheme for Feature-preserving Mesh Denoising, presented at Singapore University of Technology and Design, Singapore, 2016.
A Robust Scheme for Feature-preserving Mesh Denoising, presented at Zhejiang University, Hangzhou, China, 2015.
A Personality Model for Animating Heterogeneous Traffic Behaviors, presented at Computer Animation and Social Agents, Houston, USA, 2014.
An Accident-avoidance Full Velocity Difference Model for Animating Realistic Street-level Traffic in Rural Scenes, presented at Computer Animation and Social Agents, Istanbul, Turkey, 2013.
Academic Service
I am a reviewer of some well-known international conferences and journals, including Siggraph, Sigrraph Asia, Pacific Graphics, IEEE Transactions on Visualization and Computer Graphics, as well as Computer Animation and Virtual Worlds.

研究领域

Vision-based geometry processing/analysis""

近期论文

(1) X. Lu, ChiWang, Jun Luo,W. Chen and Y. He, Deep Nets for 3D Shape Processing. ACM Transactions on Graphics, under preparation, 2018. [First author]
(2) X. Lu, C. Zhang, Jun Luo, W. Chen and Y. He, A Robust approach for Point Cloud Filtering. IEEE Transactions on Visualization and Computer Graphics, under preparation, 2018. [Joint first author]
(3) X. Lu, Z. Fang, Jun Luo and Y. He, Convolutional Neural Networks for 3D Shape Analysis. ACM Transactions on Graphics, under preparation, 2018. [First author]
(4) W. Pan, X. Lu, Y. Gong, W. Tang, J. Liu, Y. He and G. Qiu, HLO: Half-kernel Laplacian Operator for Surface Smoothing. Under review, 2018. [Second author]
(5) Z. Shao, X. Lu, J. Cai, T. Cham and L. Ma, Task-Focused Disentanglement for Weakly-Supervised Unconstrained Action Unit Detection. Under review, 2018. [Second author]
(6) C. Zhang, X. Lu and Takuya Akashi, Blur-Countering Keypoint Detection via Eigenvalue Asymmetry. Under review, 2018. [Second author]
(7) X. Lu, S. Schaefer, Jun Luo, L. Ma and Y. He, Low Rank Matrix Approximation for Geometry Filtering. ACM Transactions on Graphics, major revision, 2018. [First author]
(8) X. Lu, Z. Deng,W. Chen and S.K. Yeung, 3D Articulated Skeleton Learning Using a Single Consumer-Grade Depth Camera. ACM Transactions on Multimedia Computing, Communications, and Applications(TOMM), major revision, 2018. [First author]
(9) X. Lu, H. Chen, S.K. Yeung, Z. Deng and W. Chen, Unsupervised Articulated Skeleton Extractionfrom Point Set Sequences Captured by a Single Depth Camera. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-2018), 2018. [First author]
(10) X. Lu, S. Wu, H. Chen, S.K. Yeung, W. Chen, M. Zwicker. GPF: GMM-inspired Feature-preserving Point Set Filtering. IEEE Transactions on Visualization and Computer Graphics, 2017. [First author]
(11) X. Lu, W. Chen, S. Schaefer. Robust Mesh Denoising via Vertex Pre-filtering and L1-Median Normal Filtering. Computer Aided Geometric Design, available online, ISSN 0167-8396, 2017. [First author]
(12) X. Lu, X. Liu, Z. Deng, W. Chen, An Efficient Approach for Feature-preserving Mesh Denoising,Optics and Lasers in Engineering, 90: 186-195, 2017. [First author]
(13) X. Lu, Z. Deng, W. Chen. A Robust Scheme for Feature-preserving Mesh Denoising. IEEE Transactionson Visualization and Computer Graphics. 22(3), 1181-1194, 2016. [First author]
(14) X. Lu, Z. Wang, M. Xu, W. Chen and Z. Deng. A Personality Model for Animating Heterogeneous Traffic Behaviors. Computer Animation and Virtual Worlds, 25(3-4): 363-373, 2014. [First author]
(15) X. Lu,W. Chen, M. Xu, Z.Wang, Z. Deng and Y. Ye. AA-FVDM: An Accident-avoidance Full Velocity Difference Model for Animating Realistic Street-level Traffic in Rural Scenes. Computer Animation and Virtual Worlds, 25(1): 83-97, 2014. [First author]
(16) K. Su, Z. Wang, X. Lu, W. Chen. An Original-stream Based Solution for Smoothly Replaying Highdefinition Videos in Desktop Virtualization Systems. Journal of Visual Languages and Computing,25(6): 676-683, 2014. [Third author]1Download the corresponding PDF via the links
(17) X. Lu, M. Xu, W. Chen, Z. Wang, and A.E. Rhalibi. Adaptive-AR Model with Drivers’ Prediction for Traffic Simulation. International Journal of Computer Games Technology, 2013: 8 pages, 2013. [First author]