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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
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
19892018
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
19872018
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
7842018
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
4052016
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
3242022
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
2952020
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
2522020
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
2482020
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
2432020
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
2372019
Domain generalization via conditional invariant representations
Y Li, M Gong, X Tian, T Liu, D Tao
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2322018
Multi-source domain adaptation: A causal view
K Zhang, M Gong, B Schölkopf
Twenty-ninth AAAI conference on artificial intelligence, 2015
2192015
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
2162017
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
2142019
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
2142018
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
1962021
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
1592021
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
1332021
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
1172018
Discovering Temporal Causal Relations from Subsampled Data.
M Gong, K Zhang, B Schoelkopf, D Tao, P Geiger
ICML, 1898-1906, 2015
1032015
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