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Jiaqian Yu
Jiaqian Yu
Samsung R&D Institute China - Beijing
Подтвержден адрес электронной почты в домене samsung.com
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Процитировано
Процитировано
Год
The eighth visual object tracking VOT2020 challenge results
M Kristan, A Leonardis, J Matas, M Felsberg, R Pflugfelder, ...
European Conference on Computer Vision, 547-601, 2020
3012020
Learning submodular losses with the Lovász hinge
J Yu, M Blaschko
International Conference on Machine Learning, 1623-1631, 2015
522015
The lovász hinge: A novel convex surrogate for submodular losses
J Yu, MB Blaschko
IEEE transactions on pattern analysis and machine intelligence 42 (3), 735-748, 2018
452018
Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
J Yu, J Xu, Y Chen, W Li, Q Wang, B Yoo, JJ Han
International Conference on Machine Learning, 12198-12207, 2021
222021
AFOD: Adaptive focused discriminative segmentation tracker
Y Chen, J Xu, J Yu, Q Wang, BI Yoo, JJ Han
European Conference on Computer Vision, 666-682, 2020
132020
A convex surrogate operator for general non-modular loss functions
J Yu, M Blaschko
Artificial Intelligence and Statistics, 1032-1041, 2016
132016
Efficient learning for discriminative segmentation with supermodular losses
J Yu, M Blaschko
British Machine Vision Conference, 2016
42016
Revisiting evaluation metrics for semantic segmentation: Optimization and evaluation of fine-grained intersection over union
Z Wang, M Berman, A Rannen-Triki, PHS Torr, D Tuia, T Tuytelaars, ...
Thirty-seventh Conference on Neural Information Processing Systems, 2023
32023
An efficient decomposition framework for discriminative segmentation with supermodular losses
J Yu, MB Blaschko
arXiv preprint arXiv:1702.03690, 2017
22017
Hardness Results for Structured Learning and Inference with Multiple Correct Outputs
M Blaschko, J Yu
Constructive Machine Learning Workshop at ICML, 2015
22015
Lovász hinge for learning submodular losses
J Yu, M Blaschko
NIPS Workshop on Representation and Learning Methods for Complex Outputs, 1-6, 2014
22014
Efficient Learning on Successive Test Time Augmentation
S Pan, J Yu, D Lee, Y Chen, C Zhang, Q Wang, BI Yoo
ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024
2024
HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Construction
Y Zhou, H Zhang, J Yu, Y Yang, S Jung, SI Park, BI Yoo
arXiv preprint arXiv:2403.08639, 2024
2024
BadTrack: A Poison-Only Backdoor Attack on Visual Object Tracking
B Huang, J Yu, Y Chen, S Pan, Q Wang, Z Wang
Advances in Neural Information Processing Systems 36, 2023
2023
Yes, IoU loss is submodular-as a function of the mispredictions
M Berman, MB Blaschko, AR Triki, J Yu
arXiv preprint arXiv:1809.01845, 2018
2018
Minimisation du risque empirique avec des fonctions de perte nonmodulaires
J Yu
Université Paris-Saclay (ComUE), 2017
2017
Empirical risk minimization with non-modular loss functions
J Yu
2017
The Lovász hinge: A convex surrogate for submodular losses
J Yu, MB Blaschko
stat 1050, 24, 2015
2015
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