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Mingming Gong
Mingming Gong
University of Melbourne & Mohamed bin Zayed University of Artificial Intelligence
Verified email at unimelb.edu.au - Homepage
Title
Cited by
Cited by
Year
Deep Ordinal Regression Network for Monocular Depth Estimation
H Fu, M Gong, C Wang, K Batmanghelich, D Tao
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
19062018
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
18752018
Deep Domain Generalization via Conditional Invariant Adversarial Networks
Y Li, X Tian, M Gong, Y Liu, T Liu, K Zhang, D Tao
Proceedings of the European Conference on Computer Vision (ECCV), 624-639, 2018
7352018
Domain Adaptation with Conditional Transferable Components
M Gong, K Zhang, T Liu, D Tao, C Glymour, B Schölkopf
Proceedings of The 33rd International Conference on Machine Learning, 2839-2848, 2016
3962016
Part-dependent label noise: Towards instance-dependent label noise
X Xia, T Liu, B Han, N Wang, M Gong, H Liu, G Niu, D Tao, M Sugiyama
Advances in Neural Information Processing Systems 33, 7597-7610, 2020
2752020
Cris: Clip-driven referring image segmentation
Z Wang, Y Lu, Q Li, X Tao, Y Guo, M Gong, T Liu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
2672022
Domain generalization via entropy regularization
S Zhao, M Gong, T Liu, H Fu, D Tao
Advances in Neural Information Processing Systems 33, 16096-16107, 2020
2342020
Sub-center arcface: Boosting face recognition by large-scale noisy web faces
J Deng, J Guo, T Liu, M Gong, S Zafeiriou
European Conference on Computer Vision, 741-757, 2020
2282020
Dual t: Reducing estimation error for transition matrix in label-noise learning
Y Yao, T Liu, B Han, M Gong, J Deng, G Niu, M Sugiyama
Advances in Neural Information Processing Systems 33, 2020
2242020
Geometry-consistent generative adversarial networks for one-sided unsupervised domain mapping
H Fu, M Gong, C Wang, K Batmanghelich, K Zhang, D Tao
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
2222019
Domain generalization via conditional invariant representations
Y Li, M Gong, X Tian, T Liu, D Tao
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2152018
Multi-source domain adaptation: A causal view
K Zhang, M Gong, B Schölkopf
Twenty-ninth AAAI conference on artificial intelligence, 2015
2152015
Geometry-aware symmetric domain adaptation for monocular depth estimation
S Zhao, H Fu, M Gong, D Tao
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
2082019
A coarse-fine network for keypoint localization
S Huang, M Gong, D Tao
Proceedings of the IEEE International Conference on Computer Vision, 3028-3037, 2017
2082017
Learning with biased complementary labels
X Yu, T Liu, M Gong, D Tao
Proceedings of the European Conference on Computer Vision (ECCV), 68-83, 2018
2042018
3d-future: 3d furniture shape with texture
H Fu, R Jia, L Gao, M Gong, B Zhao, S Maybank, D Tao
International Journal of Computer Vision, 1-25, 2021
1792021
Adaptive context-aware multi-modal network for depth completion
S Zhao, M Gong, H Fu, D Tao
IEEE Transactions on Image Processing 30, 5264-5276, 2021
1482021
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels
X Xia, T Liu, B Han, M Gong, J Yu, G Niu, M Sugiyama
arXiv preprint arXiv:2106.00445, 2021
1232021
Correcting the Triplet Selection Bias for Triplet Loss
B Yu, T Liu, M Gong, C Ding, D Tao
Proceedings of the European Conference on Computer Vision (ECCV), 71-87, 2018
1082018
Discovering Temporal Causal Relations from Subsampled Data.
M Gong, K Zhang, B Schoelkopf, D Tao, P Geiger
ICML, 1898-1906, 2015
1002015
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