@article {Wang-2017-OCNN,
title = {{O-CNN}: Octree-based Convolutional Neural Networks for {3D} Shape Analysis},
author = {Wang, Peng-Shuai and Liu, Yang and Guo, Yu-Xiao and Sun, Chun-Yu and Tong, Xin},
journal = {ACM Transactions on Graphics (SIGGRAPH)},
volume = {36},
number = {4},
year = {2017},
}
@article {Wang-2018-AOCNN,
title = {{Adaptive O-CNN}: A Patch-based Deep Representation of {3D} Shapes},
author = {Wang, Peng-Shuai and Sun, Chun-Yu and Liu, Yang and Tong, Xin},
journal = {ACM Transactions on Graphics (SIGGRAPH Asia)},
volume = {37},
number = {6},
year = {2018},
}
@InProceedings {Wang-2020-Completion,
title = {Deep Octree-based {CNNs} with Output-Guided Skip Connections for {3D} Shape and Scene Completion},
author = {Wang, Peng-Shuai and Liu, Yang and Tong, Xin},
journal = {Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2020},
}
@InProceedings {Wang2020unsupervised,
title = {Unsupervised {3D} Learning for Shape Analysis via Multiresolution Instance Discrimination},
author = {Wang, Peng-Shuai and Yang, Yu-Qi and Zou, Qian-Fang and Wu, Zhirong and Liu, Yang and Tong, Xin},
booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
year = {2021},
}
@article{Wang2020arxiv,
title = {Unsupervised {3D} Learning for Shape Analysis via Multiresolution Instance Discrimination},
author = {Wang, Peng-Shuai and Yang, Yu-Qi and Zou, Qian-Fang and Wu, Zhirong and Liu, Yang and Tong, Xin},
journal = {arXiv preprint arXiv:2008.01068},
year = {2020}
}