| Deep subspace clustering networks P Ji, T Zhang, H Li, M Salzmann, I Reid NeurIPS 2017: Conference on Neural Information Processing Systems (NeurIPS …, 2017 | 529 | 2017 |
| Efficient dense subspace clustering P Ji, M Salzmann, H Li WACV 2014: IEEE Winter Conference on Applications of Computer Vision, 2014 | 164 | 2014 |
| Incremental Learning Using Conditional Adversarial Networks Y Xiang, Y Fu, P Ji, H Huang ICCV 2019: International Conference on Computer Vision (ICCV), 2019 | 122 | 2019 |
| Invertible denoising network: A light solution for real noise removal Y Liu, Z Qin, S Anwar, P Ji, D Kim, S Caldwell, T Gedeon Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 110 | 2021 |
| Fast stereo matching using adaptive guided filtering Q Yang, P Ji, D Li, S Yao, M Zhang Image and Vision Computing 32 (3), 202-211, 2014 | 104 | 2014 |
| Shape interaction matrix revisited and robustified: Efficient subspace clustering with corrupted and incomplete data P Ji, M Salzmann, H Li ICCV 2015: Proceedings of the IEEE International Conference on Computer …, 2015 | 80 | 2015 |
| Neural collaborative subspace clustering T Zhang, P Ji(*), M Harandi, W Huang, H Li ICML 2019: International Conference on Machine Learning (ICML), 2019 | 74 | 2019 |
| Learning monocular visual odometry via self-supervised long-term modeling Y Zou, P Ji, QH Tran, JB Huang, M Chandraker ECCV 2020: European Conference on Computer Vision, 2020 | 70 | 2020 |
| Noise-aware unsupervised deep lidar-stereo fusion X Cheng(*), Y Zhong(*), Y Dai, P Ji, H Li CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 67 | 2019 |
| Unsupervised deep epipolar flow for stationary or dynamic scenes Y Zhong, P Ji, J Wang, Y Dai, H Li CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 65 | 2019 |
| Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction L Tiwari, P Ji, QH Tran, B Zhuang, S Anand, M Chandraker ECCV 2020: European Conference on Computer Vision, 2020 | 63 | 2020 |
| Displacement-invariant matching cost learning for accurate optical flow estimation J Wang, Y Zhong, Y Dai, K Zhang, P Ji, H Li NeurIPS 2020: Conference on Neural Information Processing Systems (NeurIPS), 2020 | 61 | 2020 |
| Adaptive low-rank kernel subspace clustering P Ji, I Reid, R Garg, H Li, M Salzmann arXiv preprint arXiv:1707.04974, 2017 | 48* | 2017 |
| Learning structure-and-motion-aware rolling shutter correction B Zhuang, QH Tran, P Ji, LF Cheong, M Chandraker CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 45 | 2019 |
| Monoindoor: Towards good practice of self-supervised monocular depth estimation for indoor environments P Ji, R Li, B Bhanu, Y Xu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 43 | 2021 |
| Fusing higher-order features in graph neural networks for skeleton-based action recognition Z Qin, Y Liu, P Ji, D Kim, L Wang, RI McKay, S Anwar, T Gedeon IEEE Transactions on Neural Networks and Learning Systems, 2022 | 41 | 2022 |
| Scalable deep k-subspace clustering T Zhang, P Ji, M Harandi, R Hartley, I Reid ACCV 2018: Asian Conference on Computer Vision (ACCV), 2018 | 41 | 2018 |
| Robust motion segmentation with unknown correspondences P Ji, H Li, M Salzmann, Y Dai ECCV 2014: European conference on computer vision, 204-219, 2014 | 40 | 2014 |
| Cross-Modality 3D Object Detection M Zhu, C Ma, P Ji, X Yang WACV 2020: IEEE Winter Conference on Applications of Computer Vision, 2020 | 29 | 2020 |
| Attention in attention networks for person retrieval P Fang, J Zhou, SK Roy, P Ji, L Petersson, M Harandi IEEE transactions on pattern analysis and machine intelligence 44 (9), 4626-4641, 2021 | 21 | 2021 |
Hongdong LiProfessor of Computer Vision and Learning, Australian National UniversityVerified email at anu.edu.au
