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.
Fang, Qihang; Yin, Yingda; Fan, Qingnan; Xia, Fei; Dong, Siyan; Wang, Sheng; Wang, Jue; Guibas, Leonidas J.; Chen, Baoquan: Towards Accurate Active Camera Localization. In: Lecture Notes in Computer Science. Springer Nature Switzerland, 2022 mehr…BibTeX
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Ren, Hanxiang; Yang, Yanchao; Wang, He; Shen, Bokui; Fan, Qingnan; Zheng, Youyi; Liu, C. Karen; Guibas, Leonidas: ADeLA: Automatic Dense Labeling with Attention for Viewpoint Shift in Semantic Segmentation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2022 mehr…BibTeX
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Sajnani, Rahul; Poulenard, Adrien; Jain, Jivitesh; Dua, Radhika; Guibas, Leonidas J.; Sridhar, Srinath: ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes. , 2022 mehr…BibTeX
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Wang, Yian; Wu, Ruihai; Mo, Kaichun; Ke, Jiaqi; Fan, Qingnan; Guibas, Leonidas J.; Dong, Hao: AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-Shot Interactions. In: Lecture Notes in Computer Science. Springer Nature Switzerland, 2022 mehr…BibTeX
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Zhao, Yongheng; Fang, Guangchi; Guo, Yulan; Guibas, Leonidas; Tombari, Federico; Birdal, Tolga: 3DPointCaps++: Learning 3D Representations with Capsule Networks. International Journal of Computer Vision 130 (9), 2022, 2321-2336 mehr…BibTeX
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Zheng, Yang; Yang, Yanchao; Mo, Kaichun; Li, Jiaman; Yu, Tao; Liu, Yebin; Liu, C. Karen; Guibas, Leonidas J.: GIMO: Gaze-Informed Human Motion Prediction in Context. , 2022 mehr…BibTeX
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2021
Chen, Jiayi; Yin, Yingda; Birdal, Tolga; Chen, Baoquan; Guibas, Leonidas; Wang, He: Projective Manifold Gradient Layer for Deep Rotation Regression. , 2021 mehr…BibTeX
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Gojcic, Zan; Litany, Or; Wieser, Andreas; Guibas, Leonidas J.; Birdal, Tolga: Weakly Supervised Learning of Rigid 3D Scene Flow. , 2021 mehr…BibTeX
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Huang, Jiahui; Wang, He; Birdal, Tolga; Sung, Minhyuk; Arrigoni, Federica; Hu, Shi-Min; Guibas, Leonidas: MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization. , 2021 mehr…BibTeX
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Koo, Juil; Huang, Ian; Achlioptas, Panos; Guibas, Leonidas; Sung, Minhyuk: PartGlot: Learning Shape Part Segmentation from Language Reference Games. , 2021 mehr…BibTeX
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Leszczyk, Aleksandra; Máté, Mihály; Legeza, Örs; Boguslawski, Katharina: Assessing the Accuracy of Tailored Coupled Cluster Methods Corrected by Electronic Wave Functions of Polynomial Cost. Journal of Chemical Theory and Computation 18 (1), 2021, 96-117 mehr…BibTeX
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Li, Qi; Mo, Kaichun; Yang, Yanchao; Zhao, Hang; Guibas, Leonidas: IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes. , 2021 mehr…BibTeX
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Pan, Chuanyu; Yang, Yanchao; Mo, Kaichun; Duan, Yueqi; Guibas, Leonidas: Object Pursuit: Building a Space of Objects via Discriminative Weight Generation. , 2021 mehr…BibTeX
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Shen, Yuefan; Yang, Yanchao; Yan, Mi; Wang, He; Zheng, Youyi; Guibas, Leonidas: Domain Adaptation on Point Clouds via Geometry-Aware Implicits. , 2021 mehr…BibTeX
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Shen, Yuefan; Yang, Yanchao; Zheng, Youyi; Liu, C. Karen; Guibas, Leonidas: DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis. , 2021 mehr…BibTeX
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Weng, Yijia; Wang, He; Zhou, Qiang; Qin, Yuzhe; Duan, Yueqi; Fan, Qingnan; Chen, Baoquan; Su, Hao; Guibas, Leonidas J.: CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds. , 2021 mehr…BibTeX
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Qi, Charles R.; Chen, Xinlei; Litany, Or; Guibas, Leonidas J.: ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes. 2020 mehr…BibTeX
Wang, He; Cong, Yezhen; Litany, Or; Gao, Yue; Guibas, Leonidas J.: 3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection. , 2020 mehr…BibTeX
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Xiaolong Li, He Wang, Li Yi, Leonidas J. Guibas, A. Lynn Abbott, Shuran Song: Category-Level Articulated Object Pose Estimation. CVPR 2020, 2020, 3703-3712 mehr…BibTeX
2019
Angela Dai, Christian Diller, Matthias Nießner: SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans. 2019 mehr…BibTeX
Dahnert, Manuel; Dai, Angela; Guibas, Leonidas; Nießner, Matthias: Joint Embedding of 3D Scan and CAD Objects. 2019 mehr…BibTeX
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. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, 2019, pp. 2642-2651 mehr…BibTeX
Jingwei Huang, Haotian Zhang, Li Yi, Thomas Funkhouser, Matthias Niessner, Leonidas J. Guibas: TextureNet: Consistent Local Parametrizations for Learning From High-Resolution Signals on Meshes. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, 2019, pp. 4440-4449 mehr…BibTeX
Manuel Dahnert, Angela Dai, Leonidas Guibas, Matthias Nießner: Joint Embedding of 3D Scan and CAD Objects. 2019 mehr…BibTeX
Qi, Charles R.; Litany, Or; He, Kaiming; Guibas, Leonidas J.: Deep Hough Voting for 3D Object Detection in Point Clouds. 2019 mehr…BibTeX
2018
Ganapathi-Subramanian, Vignesh; Diamanti, Olga; Pirk, Soeren; Tang, Chengcheng; Niessner, Matthias; Guibas, Leonidas: Parsing Geometry Using Structure-Aware Shape Templates. 2018 International Conference on 3D Vision (3DV), IEEE, 2018 mehr…BibTeX
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Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas Guibas: PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. 2018 mehr…BibTeX
Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas Guibas: PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. Proceedings of the International Conference on Learning Representations, 2018 mehr…BibTeX
Jingwei Huang, Haotian Zhang, Li Yi, Thomas Funkhouser, Matthias Nießner, Leonidas Guibas: TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes. 2018 mehr…BibTeX
Thies, Justus; Zollhöfer, Michael; Stamminger, Marc; Theobalt, Christian; Nießner, Matthias: Face2Face. Communications of the ACM 62 (1), 2018, 96-104 mehr…BibTeX
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Yi, Li; Zhao, Wang; Wang, He; Sung, Minhyuk; Guibas, Leonidas: GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud. 2018 mehr…BibTeX
