Kaichun Mo
Title
Cited by
Cited by
Year
Pointnet: Deep learning on point sets for 3d classification and segmentation
CR Qi, H Su, K Mo, LJ Guibas
Proceedings of the IEEE conference on computer vision and pattern …, 2017
21362017
Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding
K Mo, S Zhu, AX Chang, L Yi, S Tripathi, LJ Guibas, H Su
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
372019
Structurenet: Hierarchical graph networks for 3d shape generation
K Mo, P Guerrero, L Yi, H Su, P Wonka, N Mitra, LJ Guibas
Siggraph Asia 2019, 2019
132019
The adobeindoornav dataset: Towards deep reinforcement learning based real-world indoor robot visual navigation
K Mo, H Li, Z Lin, JY Lee
arXiv preprint arXiv:1802.08824, 2018
102018
Accelerating Random Kaczmarz Algorithm Based on Clustering Information
Y Li, K Mo, H Ye
AAAI 2016, 2015
32015
StructEdit: Learning Structural Shape Variations
K Mo, P Guerrero, L Yi, H Su, P Wonka, N Mitra, LJ Guibas
arXiv preprint arXiv:1911.11098, 2019
12019
Learning 3D Part Assembly from a Single Image
Y Li, K Mo, L Shao, M Sung, L Guibas
arXiv preprint arXiv:2003.09754, 2020
2020
SAPIEN: A SimulAted Part-based Interactive ENvironment
F Xiang, Y Qin, K Mo, Y Xia, H Zhu, F Liu, M Liu, H Jiang, Y Yuan, H Wang, ...
arXiv preprint arXiv:2003.08515, 2020
2020
PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions
K Mo, H Wang, X Yan, LJ Guibas
arXiv preprint arXiv:2003.08624, 2020
2020
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories
T Luo, K Mo, Z Huang, J Xu, S Hu, L Wang, H Su
International Conference on Learning Representations (ICLR), 2020
2020
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