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Mehdi Nourbakhsh | Shingo Murata | Kai-Hung Chang | Jieliang Luo | Chin-Yi Cheng | Yoshito Tsuji | Jieliang Luo | Chin-Yi Cheng | Kai-Hung Chang | Shingo Murata | M. Nourbakhsh | Yoshito Tsuji
[1] Jiajun Wu,et al. Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling , 2016, NIPS.
[2] Yang Liu,et al. Adaptive O-CNN: A Patch-based Deep Representation of 3D Shapes , 2018 .
[3] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[4] Christopher D. Manning,et al. Get To The Point: Summarization with Pointer-Generator Networks , 2017, ACL.
[5] Gernot Riegler,et al. OctNet: Learning Deep 3D Representations at High Resolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Navdeep Jaitly,et al. Pointer Networks , 2015, NIPS.
[7] F. Lafarge,et al. Connect-and-Slice: An Hybrid Approach for Reconstructing 3D Objects , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[8] S. M. Ali Eslami,et al. PolyGen: An Autoregressive Generative Model of 3D Meshes , 2020, ICML.
[9] Henry Howard-Jenkins,et al. Thinking Outside the Box: Generation of Unconstrained 3D Room Layouts , 2018, ACCV.
[10] Sepp Hochreiter,et al. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.
[11] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[12] Peter Wonka,et al. PolyFit: Polygonal Surface Reconstruction from Point Clouds , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[13] Song-Chun Zhu,et al. Learning Descriptor Networks for 3D Shape Synthesis and Analysis , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[14] V. Lepetit,et al. General 3D Room Layout from a Single View by Render-and-Compare , 2020, ECCV.
[15] Rui Tang,et al. Data-driven interior plan generation for residential buildings , 2019, ACM Trans. Graph..
[16] Laurens van der Maaten,et al. 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[17] Hao Zhang,et al. Graph2Plan , 2020, ACM Trans. Graph..
[18] Hao Zhang,et al. BSP-Net: Generating Compact Meshes via Binary Space Partitioning , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Greg Mori,et al. House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation , 2020, ECCV.
[20] Song Han,et al. Point-Voxel CNN for Efficient 3D Deep Learning , 2019, NeurIPS.
[21] Hao Zhang,et al. LayoutGMN: Neural Graph Matching for Structural Layout Similarity , 2020, ArXiv.
[22] Jianxiong Xiao,et al. 3D ShapeNets: A deep representation for volumetric shapes , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Peter Wonka,et al. Generative Layout Modeling using Constraint Graphs , 2020, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[24] Vladlen Koltun,et al. Computer-generated residential building layouts , 2010, SIGGRAPH 2010.
[25] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[26] Silvio Savarese,et al. 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[27] David Meger,et al. Improved Adversarial Systems for 3D Object Generation and Reconstruction , 2017, CoRL.
[28] Laurens van der Maaten,et al. Submanifold Sparse Convolutional Networks , 2017, ArXiv.
[29] Pengqian Yu,et al. End-to-end Generative Floor-plan and Layout with Attributes and Relation Graph , 2020, ArXiv.
[30] Dong-Ming Yan,et al. Generating and exploring good building layouts , 2013, ACM Trans. Graph..