Scientific Report on TUM-IAS Fellowship
We in the Visual Computing Focus Group are research enthusiasts pushing the state of the art at the intersection of computer vision, graphics, and machine learning. Our research mission is to obtain high-quality digital models of the real world, which include detailed geometry, surface texture, and material in both static and dynamic environments. full report
Short CV
Leonidas Guibas is the Paul Pigott Professor of Computer Science (and by courtesy), Electrical Engineering at Stanford University, where he heads the Geometric Computation group. Dr. Guibas obtained his Ph.D. from Stanford University under the supervision of Donald Knuth. His main subsequent employers were Xerox PARC, DEC/SRC, MIT, and Stanford. He has also held appointments at the National U. of Singapore, ETH Zurich, U. of Athens, Google Research, the Advanced Study Institute at Hong Kong University of Science and Technology, the Tsinghua-Berkeley Shenzhen Institute, and Facabook AI Research. At Stanford he is a member and past acting director of the Stanford Artificial Intelligence Laboratory and a member of the Computer Graphics Laboratory, the Institute for Computational and Mathematical Engineering (iCME) and the Bio-X program. Dr. Guibas has been elected to the US National Academy of Engineering and the American Academy of Arts and Sciences, and is an ACM Fellow, an IEEE Fellow and winner of the ACM Allen Newell award and the ICCV Helmholtz prize. He is also a recent recipient of a DoD Vannevar Bush Faculty Fellowship and a Technical University of Munich Hans Fischer Senior Fellowship.
Selected Awards
- 2018, Technical University of Munich Hans Fischer Senior Fellow
- 2018, Vannevar Bush Faculty Fellow
- 2018, Member, American Academy of Arts and Sciences
- 2017, Member, National Academy of Engineering
- 2015, IEEE Fellow
- 1999, ACM Fellow
Research Interests
Professor Guibas has a long record of theoretical and experimental work in computer science and applied mathematics. His research centers on algorithms for sensing, modeling, reasoning, rendering, and acting on the physical world. Professor Guibas' interests span computer vision, computer graphics, machine learning, computational geometry, geometric modeling, sensor networks, robotics, and discrete algorithms --- all areas in which he has published and lectured extensively.
Current areas of active research include:
- 3D computer vision: deep architectures for processing 3D data, including shape and scene analysis
- generative models for shape synthesis, ab initio or conditional
- learning over spatiotemporal data and multi-modal sensor combinations (e.g., geometry and appearance)
- the interaction of language and geometry
- joint learning over data, tasks, and representations for reduced supervision
Selected Publications
- He Wang, Sören Pirk, Ersin Yumer, Vladimir G. Kim, Ozan Sener, Srinath Sridhar, Leonidas J. Guibas. Learning a Generative Model for Multi-Step Human-Object Interactions from Videos. Comput. Graph. Forum 38(2): 367-378 (2019).
- Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, Hao Su. PartNet: A Large-Scale Benchmark for Fine-Grained and Hierarchical Part-Level 3D Object Understanding. CVPR 2019: 909-918.
- He Wang, Srinath Sridhar, Jingwei Huang, Julien Valentin, Shuran Song, Leonidas J. Guibas. Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation. CVPR 2019: 2642-2651.
- Charles R. Qi, Or Litany, Kaiming He, Leonidas J. Guibas. Deep Hough Voting for 3D Object Detection in Point Clouds. ICCV (2019).
- [update for 2020]
- Minhyuk Sung, Zhenyu Jiang, Panos Achlioptas, Niloy J. Mitra, Leonidas J. Guibas. DeformSyncNet: Deformation Transfer via Synchronized Shape Deformation Spaces. ACM Trans. Graph. 39(6): 261:1-261:16 (2020).
- Zan Gojcic, Caifa Zhou, Jan D. Wegner, Leonidas J. Guibas, Tolga Birdal. Learning Multiview 3D Point Cloud Registration. CVPR 2020: 1756-1766.
- Charles R. Qi, Xinlei Chen, Or Litany, Leonidas J. Guibas: ImVoteNet. Boosting 3D Object Detection in Point Clouds with Image Votes. CVPR 2020: 4403-4412.
- Mikaela Angelina Uy, Jingwei Huang, Minhyuk Sung, Tolga Birdal, Leonidas J. Guibas. Deformation-Aware 3D Model Embedding and Retrieval. ECCV (7) 2020: 397-413.
- Saining Xie, Jiatao Gu, Demi Guo, Charles R. Qi, Leonidas J. Guibas, Or Litany. PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding. ECCV (3) 2020: 574-591.
- Davis Rempe, Tolga Birdal, Yongheng Zhao, Zan Gojcic, Srinath Sridhar, Leonidas J. Guibas. CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations. NeurIPS 2020.
Publications as TUM-IAS Fellow
