| Deep subspace clustering networks P Ji, T Zhang, H Li, M Salzmann, I Reid NeurIPS 2017: Conference on Neural Information Processing Systems (NeurIPS …, 2017 | 213 | 2017 |
| Efficient dense subspace clustering P Ji, M Salzmann, H Li WACV 2014: IEEE Winter Conference on Applications of Computer Vision, 2014 | 79 | 2014 |
| 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 | 77 | 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 | 57 | 2015 |
| Robust motion segmentation with unknown correspondences P Ji, H Li, M Salzmann, Y Dai ECCV 2014: European conference on computer vision, 204-219, 2014 | 30 | 2014 |
| Neural collaborative subspace clustering T Zhang, P Ji(*), M Harandi, W Huang, H Li ICML 2019: International Conference on Machine Learning (ICML), 2019 | 26 | 2019 |
| Incremental Learning Using Conditional Adversarial Networks Y Xiang, Y Fu, P Ji, H Huang ICCV 2019: International Conference on Computer Vision (ICCV), 2019 | 25 | 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 | 21 | 2019 |
| Adaptive low-rank kernel subspace clustering P Ji, I Reid, R Garg, H Li, M Salzmann arXiv preprint arXiv:1707.04974, 2017 | 17* | 2017 |
| An automatic 2D to 3D conversion algorithm using multi-depth cues P Ji, L Wang, DX Li, M Zhang 2012 International Conference on Audio, Language and Image Processing, 546-550, 2012 | 17 | 2012 |
| Scalable deep k-subspace clustering T Zhang, P Ji, M Harandi, R Hartley, I Reid ACCV 2018: Asian Conference on Computer Vision (ACCV), 2018 | 16 | 2018 |
| 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 | 14 | 2019 |
| 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 | 14 | 2019 |
| "Maximizing rigidity" revisited: a convex programming approach for generic 3D shape reconstruction from multiple perspective views P Ji, H Li, Y Dai, I Reid ICCV 2017: IEEE International Conference on Computer Vision (ICCV), 2017 | 13 | 2017 |
| Robust multi-body feature tracker: a segmentation-free approach P Ji, H Li, M Salzmann, Y Zhong CVPR 2016: Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 12 | 2016 |
| 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 | 10 | 2020 |
| 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 | 7 | 2020 |
| Null space clustering with applications to motion segmentation and face clustering P Ji, Y Zhong, H Li, M Salzmann 2014 IEEE International Conference on Image Processing (ICIP), 283-287, 2014 | 6 | 2014 |
| 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 | 5 | 2020 |
| Understanding Road Layout From Videos as a Whole B Liu, B Zhuang, S Schulter, P Ji, M Chandraker CVPR 2020: Proceedings of the IEEE/CVF Conference on Computer Vision and …, 2020 | 2 | 2020 |
Hongdong LiAustralian National UniversityVerified email at anu.edu.au
