Folgen
Shuang Li(李爽)
Shuang Li(李爽)
Associate Professor in School of Computer Science and Technology, Beijing Institute of Technology
Bestätigte E-Mail-Adresse bei bit.edu.cn - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Domain invariant and class discriminative feature learning for visual domain adaptation
S Li, S Song, G Huang, Z Ding, C Wu
IEEE transactions on image processing 27 (9), 4260-4273, 2018
2562018
Causality inspired representation learning for domain generalization
F Lv, J Liang, S Li, B Zang, CH Liu, Z Wang, D Liu
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
1762022
Deep residual correction network for partial domain adaptation
S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang, Z Ding
IEEE transactions on pattern analysis and machine intelligence 43 (7), 2329-2344, 2020
1732020
Metasaug: Meta semantic augmentation for long-tailed visual recognition
S Li, K Gong, CH Liu, Y Wang, F Qiao, X Cheng
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
1712021
Domain adaptation via prompt learning
C Ge, R Huang, M Xie, Z Lai, S Song, S Li, G Huang
IEEE Transactions on Neural Networks and Learning Systems, 2023
1622023
SOE-Net: A self-attention and orientation encoding network for point cloud based place recognition
Y Xia, Y Xu, S Li, R Wang, J Du, D Cremers, U Stilla
Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2021
1562021
Sepico: Semantic-guided pixel contrast for domain adaptive semantic segmentation
B Xie, S Li, M Li, CH Liu, G Huang, G Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
1552023
Transferable semantic augmentation for domain adaptation
S Li, M Xie, K Gong, CH Liu, Y Wang, W Li
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
1472021
Joint adversarial domain adaptation
S Li, CH Liu, B Xie, L Su, Z Ding, G Huang
Proceedings of the 27th ACM International Conference on Multimedia, 729-737, 2019
1282019
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation
S Li, F Lv, B Xie, CH Liu, J Liang, C Qin
arXiv preprint arXiv:2012.06995, 2020
1242020
Active learning for domain adaptation: An energy-based approach
B Xie, L Yuan, S Li, CH Liu, X Cheng, G Wang
Proceedings of the AAAI conference on artificial intelligence 36 (8), 8708-8716, 2022
1162022
Domain space transfer extreme learning machine for domain adaptation
Y Chen, S Song, S Li, L Yang, C Wu
IEEE Transactions on Cybernetics 49 (5), 1909-1922, 2018
1132018
Domain conditioned adaptation network
S Li, C Liu, Q Lin, B Xie, Z Ding, G Huang, J Tang
Proceedings of the AAAI conference on artificial intelligence 34 (07), 11386 …, 2020
1122020
Semantic concentration for domain adaptation
S Li, M Xie, F Lv, CH Liu, J Liang, C Qin, W Li
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
1072021
Robust test-time adaptation in dynamic scenarios
L Yuan, B Xie, S Li
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
962023
Towards fewer annotations: Active learning via region impurity and prediction uncertainty for domain adaptive semantic segmentation
B Xie, L Yuan, S Li, CH Liu, X Cheng
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
942022
Prediction reweighting for domain adaptation
S Li, S Song, G Huang
IEEE transactions on neural networks and learning systems 28 (7), 1682-1695, 2016
872016
A graph embedding framework for maximum mean discrepancy-based domain adaptation algorithms
Y Chen, S Song, S Li, C Wu
IEEE Transactions on Image Processing 29, 199-213, 2019
802019
Discriminative transfer feature and label consistency for cross-domain image classification
S Li, CH Liu, L Su, B Xie, Z Ding, CLP Chen, D Wu
IEEE Transactions on Neural Networks and Learning Systems 31 (11), 4842-4856, 2020
702020
Generalized domain conditioned adaptation network
S Li, B Xie, Q Lin, CH Liu, G Huang, G Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (8), 4093-4109, 2021
682021
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20