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Books and Theses
- 2019
[b1]Xialei Liu:
Visual recognition in the wild: learning from rankings in small domains and continual learning in new domains. Autonomous University of Barcelona, Spain, 2019
Journal Articles
- 2024
- [j5]Wei-Hong Li
, Xialei Liu, Hakan Bilen:
Universal Representations: A Unified Look at Multiple Task and Domain Learning. Int. J. Comput. Vis. 132(5): 1521-1545 (2024) - 2023
- [j4]Zheng Lin, Zhao Zhang, Ziyue Zhu, Deng-Ping Fan, Xialei Liu:
Sequential interactive image segmentation. Comput. Vis. Media 9(4): 753-765 (2023) - [j3]Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer:
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5513-5533 (2023) - [j2]Lu Yu, Xialei Liu, Joost van de Weijer:
Self-Training for Class-Incremental Semantic Segmentation. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9116-9127 (2023) - 2019
- [j1]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank. IEEE Trans. Pattern Anal. Mach. Intell. 41(8): 1862-1878 (2019)
Conference and Workshop Papers
- 2024
- [c26]Jiang-Tian Zhai, Xialei Liu, Lu Yu, Ming-Ming Cheng:
Fine-Grained Knowledge Selection and Restoration for Non-exemplar Class Incremental Learning. AAAI 2024: 6971-6978 - [c25]Xialei Liu, Jiang-Tian Zhai, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng:
Task-Adaptive Saliency Guidance for Exemplar-Free Class Incremental Learning. CVPR 2024: 23954-23963 - [c24]Xusheng Cao, Haori Lu, Linlan Huang, Xialei Liu, Ming-Ming Cheng:
Generative Multi-modal Models are Good Class-Incremental Learners. CVPR 2024: 28706-28717 - [c23]Zhimao Peng, Enguang Wang, Xialei Liu, Ming-Ming Cheng:
Let's Start Over: Retraining with Selective Samples for Generalized Category Discovery. IJCAI 2024: 4815-4823 - [c22]Yusong Hu, Yuting Gao, Zihan Xu, Ke Li, Xialei Liu:
A3R: Vision Language Pre-training by Attentive Alignment and Attentive Reconstruction. PRCV (5) 2024: 129-142 - 2023
- [c21]Jia-Wen Xiao, Chang-Bin Zhang, Jiekang Feng, Xialei Liu, Joost van de Weijer, Ming-Ming Cheng:
Endpoints Weight Fusion for Class Incremental Semantic Segmentation. CVPR 2023: 7204-7213 - [c20]Yuyang Liu, Yang Cong, Dipam Goswami, Xialei Liu, Joost van de Weijer:
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. ICCV 2023: 11333-11343 - [c19]Xin Jin, Jia-Wen Xiao, Linghao Han, Chunle Guo, Ruixun Zhang, Xialei Liu, Chongyi Li:
Lighting Every Darkness in Two Pairs : A Calibration-Free Pipeline for RAW Denoising. ICCV 2023: 13229-13238 - [c18]Jiang-Tian Zhai, Xialei Liu, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng:
Masked Autoencoders are Efficient Class Incremental Learners. ICCV 2023: 19047-19056 - 2022
- [c17]Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer:
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. BMVC 2022: 38 - [c16]Kai Wang, Xialei Liu, Andy Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer:
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. CVPR Workshops 2022: 3728-3738 - [c15]Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng:
Representation Compensation Networks for Continual Semantic Segmentation. CVPR 2022: 7043-7054 - [c14]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Cross-domain Few-shot Learning with Task-specific Adapters. CVPR 2022: 7151-7160 - [c13]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Learning Multiple Dense Prediction Tasks from Partially Annotated Data. CVPR 2022: 18857-18867 - [c12]Xialei Liu, Yusong Hu, Xu-Sheng Cao, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng:
Long-Tailed Class Incremental Learning. ECCV (33) 2022: 495-512 - 2021
- [c11]Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer:
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. BMVC 2021: 119 - [c10]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Universal Representation Learning from Multiple Domains for Few-shot Classification. ICCV 2021: 9506-9515 - 2020
- [c9]Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer:
Generative Feature Replay For Class-Incremental Learning. CVPR Workshops 2020: 915-924 - [c8]Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer:
Semantic Drift Compensation for Class-Incremental Learning. CVPR 2020: 6980-6989 - [c7]Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu:
Learning to Rank for Active Learning: A Listwise Approach. ICPR 2020: 5587-5594 - 2019
- [c6]Lu Yu, Vacit Oguz Yazici, Xialei Liu, Joost van de Weijer, Yongmei Cheng, Arnau Ramisa:
Learning Metrics From Teachers: Compact Networks for Image Embedding. CVPR 2019: 2907-2916 - 2018
- [c5]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. CVPR 2018: 7661-7669 - [c4]Xialei Liu, Marc Masana, Luis Herranz, Joost van de Weijer, Antonio M. López, Andrew D. Bagdanov:
Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting. ICPR 2018: 2262-2268 - [c3]Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost van de Weijer, Bogdan Raducanu:
Memory Replay GANs: Learning to Generate New Categories without Forgetting. NeurIPS 2018: 5966-5976 - 2017
- [c2]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
RankIQA: Learning from Rankings for No-Reference Image Quality Assessment. ICCV 2017: 1040-1049 - 2015
- [c1]Lu Yu, Yongmei Cheng, Xialei Liu, Nan Liu:
Suitability of Real-Time Image under Complicated Environment Based on Contourlet in SMN. ISKE 2015: 485-488
Informal and Other Publications
- 2024
- [i31]Enguang Wang, Zhimao Peng, Zhengyuan Xie, Xialei Liu, Ming-Ming Cheng:
GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery. CoRR abs/2403.09974 (2024) - [i30]Xusheng Cao, Haori Lu, Linlan Huang, Xialei Liu, Ming-Ming Cheng:
Generative Multi-modal Models are Good Class-Incremental Learners. CoRR abs/2403.18383 (2024) - [i29]Zhengyuan Xie, Haiquan Lu, Jia-Wen Xiao, Enguang Wang, Le Zhang, Xialei Liu:
Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation. CoRR abs/2407.14142 (2024) - [i28]Linlan Huang, Xusheng Cao, Haori Lu, Xialei Liu:
Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion. CoRR abs/2407.14143 (2024) - 2023
- [i27]Yuyang Liu, Yang Cong, Dipam Goswami, Xialei Liu, Joost van de Weijer:
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. CoRR abs/2307.12427 (2023) - [i26]Xin Jin, Jia-Wen Xiao, Linghao Han, Chunle Guo, Ruixun Zhang, Xialei Liu, Chongyi Li:
Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising. CoRR abs/2308.03448 (2023) - [i25]Jiang-Tian Zhai, Xialei Liu, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng:
Masked Autoencoders are Efficient Class Incremental Learners. CoRR abs/2308.12510 (2023) - [i24]Xialei Liu, Xusheng Cao, Haori Lu, Jia-Wen Xiao, Andrew D. Bagdanov, Ming-Ming Cheng:
Class Incremental Learning with Pre-trained Vision-Language Models. CoRR abs/2310.20348 (2023) - [i23]Jiang-Tian Zhai, Xialei Liu, Lu Yu, Ming-Ming Cheng:
Fine-Grained Knowledge Selection and Restoration for Non-Exemplar Class Incremental Learning. CoRR abs/2312.12722 (2023) - 2022
- [i22]Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng:
Representation Compensation Networks for Continual Semantic Segmentation. CoRR abs/2203.05402 (2022) - [i21]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Universal Representations: A Unified Look at Multiple Task and Domain Learning. CoRR abs/2204.02744 (2022) - [i20]Xialei Liu, Yusong Hu, Xu-Sheng Cao, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng:
Long-Tailed Class Incremental Learning. CoRR abs/2210.00266 (2022) - [i19]Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer:
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. CoRR abs/2210.01600 (2022) - [i18]Xialei Liu, Jiang-Tian Zhai, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng:
Robust Saliency Guidance for Data-free Class Incremental Learning. CoRR abs/2212.08251 (2022) - 2021
- [i17]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Universal Representation Learning from Multiple Domains for Few-shot Classification. CoRR abs/2103.13841 (2021) - [i16]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Improving Task Adaptation for Cross-domain Few-shot Learning. CoRR abs/2107.00358 (2021) - [i15]Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer:
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. CoRR abs/2110.11148 (2021) - [i14]Kai Wang, Xialei Liu, Andrew D. Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer:
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. CoRR abs/2111.04993 (2021) - [i13]Wei-Hong Li, Xialei Liu, Hakan Bilen:
Learning Multiple Dense Prediction Tasks from Partially Annotated Data. CoRR abs/2111.14893 (2021) - 2020
- [i12]Xialei Liu, Hao Yang, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto:
Continual Universal Object Detection. CoRR abs/2002.05347 (2020) - [i11]Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer:
Semantic Drift Compensation for Class-Incremental Learning. CoRR abs/2004.00440 (2020) - [i10]Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer:
Generative Feature Replay For Class-Incremental Learning. CoRR abs/2004.09199 (2020) - [i9]Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu:
Learning to Rank for Active Learning: A Listwise Approach. CoRR abs/2008.00078 (2020) - [i8]Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer:
Class-incremental learning: survey and performance evaluation. CoRR abs/2010.15277 (2020) - [i7]Lu Yu, Xialei Liu, Joost van de Weijer:
Self-Training for Class-Incremental Semantic Segmentation. CoRR abs/2012.03362 (2020) - 2019
- [i6]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank. CoRR abs/1902.06285 (2019) - [i5]Lu Yu, Vacit Oguz Yazici, Xialei Liu, Joost van de Weijer, Yongmei Cheng, Arnau Ramisa:
Learning Metrics from Teachers: Compact Networks for Image Embedding. CoRR abs/1904.03624 (2019) - 2018
- [i4]Xialei Liu, Marc Masana, Luis Herranz, Joost van de Weijer, Antonio M. López, Andrew D. Bagdanov:
Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting. CoRR abs/1802.02950 (2018) - [i3]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. CoRR abs/1803.03095 (2018) - [i2]Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost van de Weijer, Bogdan Raducanu:
Memory Replay GANs: learning to generate images from new categories without forgetting. CoRR abs/1809.02058 (2018) - 2017
- [i1]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
RankIQA: Learning from Rankings for No-reference Image Quality Assessment. CoRR abs/1707.08347 (2017)
Coauthor Index
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