Xialei Liu

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 57

Top Topics

Incremental Learning

Quality Assessment

Learning To Rank

Top Venues

Publications

Linlan Huang, Xusheng Cao, Haori Lu, Xialei Liu
Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion. CoRR (2024)
Jiang-Tian Zhai, Xialei Liu, Lu Yu, Ming-Ming Cheng
Fine-Grained Knowledge Selection and Restoration for Non-exemplar Class Incremental Learning. AAAI (2024)
Enguang Wang, Zhimao Peng, Zhengyuan Xie, Xialei Liu, Ming-Ming Cheng
GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery. CoRR (2024)
Xu-Sheng Cao, Haori Lu, Linlan Huang, Xialei Liu, Ming-Ming Cheng
Generative Multi-modal Models are Good Class-Incremental Learners. CoRR (2024)
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 (2024)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Universal Representations: A Unified Look at Multiple Task and Domain Learning. Int. J. Comput. Vis. 132 (5) (2024)
Lu Yu, Xialei Liu, Joost van de Weijer
Self-Training for Class-Incremental Semantic Segmentation. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
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)
Xialei Liu, Xu-Sheng Cao, Haori Lu, Jia-Wen Xiao, Andrew D. Bagdanov, Ming-Ming Cheng
Class Incremental Learning with Pre-trained Vision-Language Models. CoRR (2023)
Jiang-Tian Zhai, Xialei Liu, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng
Masked Autoencoders are Efficient Class Incremental Learners. CoRR (2023)
Zheng Lin, Zhao Zhang, Ziyue Zhu, Deng-Ping Fan, Xialei Liu
Sequential interactive image segmentation. Comput. Vis. Media 9 (4) (2023)
Yuyang Liu, Yang Cong, Dipam Goswami, Xialei Liu, Joost van de Weijer
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. CoRR (2023)
Jiang-Tian Zhai, Xialei Liu, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng
Masked Autoencoders are Efficient Class Incremental Learners. ICCV (2023)
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)
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 (2023)
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) (2023)
Jiang-Tian Zhai, Xialei Liu, Lu Yu, Ming-Ming Cheng
Fine-Grained Knowledge Selection and Restoration for Non-Exemplar Class Incremental Learning. CoRR (2023)
Yuyang Liu, Yang Cong, Dipam Goswami, Xialei Liu, Joost van de Weijer
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. ICCV (2023)
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)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Cross-domain Few-shot Learning with Task-specific Adapters. CVPR (2022)
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)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Universal Representations: A Unified Look at Multiple Task and Domain Learning. CoRR (2022)
Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng
Representation Compensation Networks for Continual Semantic Segmentation. CVPR (2022)
Xialei Liu, Yu-Song Hu, Xu-Sheng Cao, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng
Long-Tailed Class Incremental Learning. CoRR (2022)
Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng
Representation Compensation Networks for Continual Semantic Segmentation. CoRR (2022)
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 (2022)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Learning Multiple Dense Prediction Tasks from Partially Annotated Data. CVPR (2022)
Xialei Liu, Yu-Song Hu, Xu-Sheng Cao, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng
Long-Tailed Class Incremental Learning. ECCV (33) (2022)
Xialei Liu, Jiang-Tian Zhai, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng
Robust Saliency Guidance for Data-free Class Incremental Learning. CoRR (2022)
Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. CoRR (2021)
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 (2021)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Improving Task Adaptation for Cross-domain Few-shot Learning. CoRR (2021)
Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. BMVC (2021)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Universal Representation Learning from Multiple Domains for Few-shot Classification. CoRR (2021)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Learning Multiple Dense Prediction Tasks from Partially Annotated Data. CoRR (2021)
Wei-Hong Li, Xialei Liu, Hakan Bilen
Universal Representation Learning from Multiple Domains for Few-shot Classification. ICCV (2021)
Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan C. Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer
Generative Feature Replay For Class-Incremental Learning. CoRR (2020)
Xialei Liu, Hao Yang, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Continual Universal Object Detection. CoRR (2020)
Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan C. Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer
Generative Feature Replay For Class-Incremental Learning. CVPR Workshops (2020)
Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer
Class-incremental learning: survey and performance evaluation. CoRR (2020)
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)
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 (2020)
Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan C. Raducanu
Learning to Rank for Active Learning: A Listwise Approach. ICPR (2020)
Lu Yu, Xialei Liu, Joost van de Weijer
Self-Training for Class-Incremental Semantic Segmentation. CoRR (2020)
Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan C. Raducanu
Learning to Rank for Active Learning: A Listwise Approach. CoRR (2020)
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) (2019)
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)
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank. CoRR (2019)
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 (2019)
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 (2018)
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)
Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost van de Weijer, Bogdan C. Raducanu
Memory Replay GANs: Learning to Generate New Categories without Forgetting. NeurIPS (2018)
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. CoRR (2018)
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. CVPR (2018)
Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost van de Weijer, Bogdan C. Raducanu
Memory Replay GANs: learning to generate images from new categories without forgetting. CoRR (2018)
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
RankIQA: Learning from Rankings for No-Reference Image Quality Assessment. ICCV (2017)
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
RankIQA: Learning from Rankings for No-reference Image Quality Assessment. CoRR (2017)
Lu Yu, Yongmei Cheng, Xialei Liu, Nan Liu
Suitability of Real-Time Image under Complicated Environment Based on Contourlet in SMN. ISKE (2015)