Pan Ji
Pan Ji
Ph.D., InnoPeak Technology
Verified email at innopeaktech.com - Homepage
Title
Cited by
Cited by
Year
Deep subspace clustering networks
P Ji, T Zhang, H Li, M Salzmann, I Reid
NeurIPS 2017: Conference on Neural Information Processing Systems (NeurIPS …, 2017
1872017
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
772014
Efficient dense subspace clustering
P Ji, M Salzmann, H Li
WACV 2014: IEEE Winter Conference on Applications of Computer Vision, 2014
712014
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
522015
Robust motion segmentation with unknown correspondences
P Ji, H Li, M Salzmann, Y Dai
ECCV 2014: European conference on computer vision, 204-219, 2014
282014
Neural collaborative subspace clustering
T Zhang, P Ji(*), M Harandi, W Huang, H Li
ICML 2019: International Conference on Machine Learning (ICML), 2019
252019
Incremental Learning Using Conditional Adversarial Networks
Y Xiang, Y Fu, P Ji, H Huang
ICCV 2019: International Conference on Computer Vision (ICCV), 2019
212019
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
172012
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
142019
Scalable deep k-subspace clustering
T Zhang, P Ji, M Harandi, R Hartley, I Reid
ACCV 2018: Asian Conference on Computer Vision (ACCV), 2018
142018
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
132019
Adaptive low-rank kernel subspace clustering
P Ji, I Reid, R Garg, H Li, M Salzmann
arXiv preprint arXiv:1707.04974, 2017
13*2017
"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
122017
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
122016
Degeneracy in self-calibration revisited and a deep learning solution for uncalibrated slam
B Zhuang, QH Tran, P Ji, GH Lee, LF Cheong, M Chandraker
arXiv preprint arXiv:1907.13185, 2019
92019
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
82019
Displacement-invariant matching cost learning for accurate optical flow estimation
J Wang, Y Zhong, Y Dai, K Zhang, P Ji, H Li
arXiv preprint arXiv:2010.14851, 2020
52020
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
52014
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
42020
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
22020
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