Segui
Jian Liang (梁坚)
Titolo
Citata da
Citata da
Anno
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
J Liang, D Hu, J Feng
International Conference on Machine Learning, 6028-6039, 2020
14192020
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-free Approach
L He, J Liang, H Li, Z Sun
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
3642018
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
M Luo, F Chen, D Hu, Y Zhang, J Liang, J Feng
Annual Conference on Neural Information Processing Systems, 5972-5984, 2021
3412021
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
J Liang, D Hu, Y Wang, R He, J Feng
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8602 …, 2022
2892022
Domain Adaptation with Auxiliary Target Domain-Oriented Classifier
J Liang, D Hu, J Feng
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
2142021
Aggregating Randomized Clustering-Promoting Invariant Projections for Domain Adaptation
J Liang, R He, Z Sun, T Tan
IEEE Transactions on Pattern Analysis and Machine Intelligence 41 (5), 1027-1042, 2019
1622019
A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts
J Liang, R He, T Tan
International Journal of Computer Vision, 2024
1592024
A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
J Liang, Y Wang, D Hu, R He, J Feng
European Conference on Computer Vision, 123-140, 2020
1492020
Exploring Uncertainty in Pseudo-label Guided Unsupervised Domain Adaptation
J Liang, R He, Z Sun, T Tan
Pattern Recognition Journal, 2019
1442019
DINE: Domain Adaptation from Single and Multiple Black-box Predictors
J Liang, D Hu, J Feng, R He
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
126*2022
Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation
J Liang, R He, Z Sun, T Tan
IEEE Conference on Computer Vision and Pattern Recognition, 2975-2984, 2019
1202019
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning
Y Shi, K Zhou, J Liang, Z Jiang, J Feng, P Torr, S Bai, VYF Tan
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
772022
Masked Relation Learning for DeepFake Detection
Z Yang, J Liang, Y Xu, XY Zhang, R He
IEEE Transactions on Information Forensics and Security 18, 1696-1708, 2023
702023
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
Y Zhang, B Hooi, D Hu, J Liang, J Feng
Annual Conference on Neural Information Processing Systems, 29848-29860, 2021
692021
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
Y Shi, J Liang, W Zhang, VYF Tan, S Bai
International Conference on Learning Representations, 2023
632023
Self-Paced Learning: an Implicit Regularization Perspective
Y Fan, R He, J Liang, BG Hu
AAAI Conference on Artificial Intelligence, 1877-1883, 2017
572017
Learning Feature Recovery Transformer for Occluded Person Re-identification
B Xu, L He, J Liang, Z Sun
IEEE Transactions on Image Processing 31, 4651-4662, 2022
562022
Diagnostic Classification for Human Autism and Obsessive-Compulsive Disorder Based on Machine Learning From a Primate Genetic Model
Y Zhan, J Wei, J Liang, X Xu, R He, TW Robbins, Z Wang
American Journal of Psychiatry 178 (1), 65-76, 2021
522021
ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation
Y Ding, L Sheng, J Liang, A Zheng, R He
Neural Networks, 2023
502023
Free Lunch for Domain Adversarial Training: Environment Label Smoothing
YF Zhang, X Wang, J Liang, Z Zhang, L Wang, R Jin, T Tan
International Conference on Learning Representations, 2023
452023
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