適用於公開取用強制性政策的文章 - Kaichun Mo瞭解詳情
在某個資料庫公開的文章：19
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
授權規定： US National Science Foundation, US Department of Defense
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/CVF conference on computer vision and pattern …, 2019
授權規定： US National Science Foundation, US Department of Defense
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, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
授權規定： US National Science Foundation, US Department of Defense
Where2Act: From Pixels to Actions for Articulated 3D Objects
K Mo, L Guibas, M Mukadam, A Gupta, S Tulsiani
International Conference on Computer Vision (ICCV) 2021, 2021
授權規定： US National Science Foundation, US Department of Defense
Generative 3D Part Assembly via Dynamic Graph Learning
J Huang, G Zhan, Q Fan, K Mo, L Shao, B Chen, L Guibas, H Dong
Advances in Neural Information Processing Systems 33 pre-proceedings …, 2020
授權規定： US Department of Defense
GIMO: Gaze-Informed Human Motion Prediction in Context
Y Zheng, Y Yang, K Mo, J Li, T Yu, Y Liu, K Liu, LJ Guibas
European Conference on Computer Vision (ECCV) 2022, 2022
授權規定： US Department of Defense, National Natural Science Foundation of China
Learning 3D Part Assembly from a Single Image
Y Li, K Mo, L Shao, M Sung, L Guibas
European Conference on Computer Vision (ECCV) 2020, 2020
授權規定： US Department of Defense
O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning
K Mo, Y Qin, F Xiang, H Su, L Guibas
Conference on Robot Learning (CoRL) 2021, 2021
授權規定： US National Science Foundation, US Department of Defense
AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions
Y Wang, R Wu, K Mo, J Ke, Q Fan, L Guibas, H Dong
European Conference on Computer Vision (ECCV) 2022, 2022
授權規定： US National Science Foundation, US Department of Defense, National Natural …
PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions
K Mo, H Wang, X Yan, LJ Guibas
European Conference on Computer Vision (ECCV) 2020, 2020
授權規定： US Department of Defense
StructEdit: Learning structural shape variations
K Mo, P Guerrero, L Yi, H Su, P Wonka, NJ Mitra, LJ Guibas
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
授權規定： US National Science Foundation, US Department of Defense, European Commission
DSG-Net: Learning Disentangled Structure and Geometry for 3D Shape Generation
J Yang, K Mo, YK Lai, LJ Guibas, L Gao
ACM Transaction on Graphics (ToG), 2020
授權規定： US National Science Foundation, US Department of Defense, Chinese Academy of …
SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation With Fine-Grained Geometry
L Gao, JM Sun, K Mo, YK Lai, LJ Guibas, J Yang
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (7), 8902-8919, 2023
授權規定： US Department of Defense, Chinese Academy of Sciences, National Natural …
Dsm-net: Disentangled structured mesh net for controllable generation of fine geometry
J Yang, K Mo, YK Lai, LJ Guibas, L Gao
arXiv preprint arXiv:2008.05440 2 (3), 2020
授權規定： US National Science Foundation, US Department of Defense, National Natural …
Where2explore: Few-shot affordance learning for unseen novel categories of articulated objects
C Ning, R Wu, H Lu, K Mo, H Dong
Advances in Neural Information Processing Systems 36, 4585-4596, 2023
授權規定： National Natural Science Foundation of China
Jacobinerf: Nerf shaping with mutual information gradients
X Xu, Y Yang, K Mo, B Pan, L Yi, L Guibas
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
授權規定： US Department of Defense
Haisor: Human-aware Indoor Scene Optimization via Deep Reinforcement Learning
JM Sun, J Yang, K Mo, YK Lai, L Guibas, L Gao
ACM Transactions on Graphics 43 (2), 1-17, 2024
授權規定： US Department of Defense, National Natural Science Foundation of China
Fixing malfunctional objects with learned physical simulation and functional prediction
Y Hong, K Mo, L Yi, LJ Guibas, A Torralba, JB Tenenbaum, C Gan
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
授權規定： US National Science Foundation, US Department of Defense
COPILOT: Human-environment collision prediction and localization from egocentric videos
B Pan, B Shen, D Rempe, D Paschalidou, K Mo, Y Yang, LJ Guibas
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
授權規定： Swiss National Science Foundation, US Department of Defense
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