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PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions.

K. Mo, H. Wang, X. Yan, и L. Guibas. ECCV (6), том 12351 из Lecture Notes in Computer Science, стр. 683-701. Springer, (2020)

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Mo Zhong

Ce Mo

Tianmin Mo

Mo Yabg

Mo Yarden

Другие публикации лиц с тем же именем

Compositionally Generalizable 3D Structure Prediction.S. Han, J. Gu, K. Mo, L. Yi, S. Hu, X. Chen, и H. Su. CoRR, (2020)IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes.Q. Li, K. Mo, Y. Yang, H. Zhao, и L. Guibas. ICLR, OpenReview.net, (2022)Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks.Y. Weng, K. Mo, R. Shi, Y. Yang, и L. Guibas. ICML, том 202 из Proceedings of Machine Learning Research, стр. 36958-36977. PMLR, (2023)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 и 4 other автор(ы). CVPR, стр. 11094-11104. Computer Vision Foundation / IEEE, (2020)GIMO: Gaze-Informed Human Motion Prediction in Context.Y. Zheng, Y. Yang, K. Mo, J. Li, T. Yu, Y. Liu, C. Liu, и L. Guibas. ECCV (13), том 13673 из Lecture Notes in Computer Science, стр. 676-694. Springer, (2022)Haisor: Human-aware Indoor Scene Optimization via Deep Reinforcement Learning.J. Sun, J. Yang, K. Mo, Y. Lai, L. Guibas, и L. Gao. ACM Trans. Graph., 43 (2): 15:1-15:17 (апреля 2024)O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning.K. Mo, Y. Qin, F. Xiang, H. Su, и L. Guibas. CoRL, том 164 из Proceedings of Machine Learning Research, стр. 1666-1677. PMLR, (2021)PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation.C. Qi, H. Su, K. Mo, и L. Guibas. CVPR, стр. 77-85. IEEE Computer Society, (2017)Object Pursuit: Building a Space of Objects via Discriminative Weight Generation.C. Pan, Y. Yang, K. Mo, Y. Duan, и L. Guibas. ICLR, OpenReview.net, (2022)Category-Level Multi-Part Multi-Joint 3D Shape Assembly.Y. Li, K. Mo, Y. Duan, H. Wang, J. Zhang, L. Shao, W. Matusik, и L. Guibas. CoRR, (2023)

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