| 3d point cloud generative adversarial network based on tree structured graph convolutions DW Shu, SW Park, J Kwon Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 289 | 2019 |
| Hierarchical bidirected graph convolutions for large-scale 3-D point cloud place recognition DW Shu, J Kwon IEEE Transactions on Neural Networks and Learning Systems, 2023 | 9 | 2023 |
| Generative adversarial networks for markovian temporal dynamics: Stochastic continuous data generation SW Park, DW Shu, J Kwon International Conference on Machine Learning, 8413-8421, 2021 | 8 | 2021 |
| Robust person re-identification via graph convolution networks G Kim, DW Shu, J Kwon Multimedia Tools and Applications 80 (19), 29129-29138, 2021 | 6 | 2021 |
| Wasserstein distributional harvesting for highly dense 3D point clouds DW Shu, SW Park, J Kwon Pattern Recognition 132, 108978, 2022 | 5 | 2022 |
| Localized curvature-based combinatorial subgraph sampling for large-scale graphs DW Shu, Y Kim, J Kwon Pattern Recognition 139, 109475, 2023 | 3 | 2023 |
| Deep-plane sweep generative adversarial network for consistent multi-view depth estimation DW Shu, W Jang, H Yoo, HC Shin, J Kwon Machine Vision and Applications 33 (1), 1-10, 2022 | 2 | 2022 |
| Deep diffusion-invariant wasserstein distributional classification SW Park, DW Shu, J Kwon Advances in Neural Information Processing Systems 33, 20697-20706, 2020 | | 2020 |
| Supplementary Materials for Generative Adversarial Networks for Markovian Temporal Dynamics SW Park, DW Shu, J Kwon | | |
| Supplementary Materials for 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions DW Shu, SW Park, J Kwon | | |
