| 2026 | AAAI | Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection. | Xinbin Yuan, Zhaohui Zheng, Yuxuan Li, Xialei Liu, Li Liu, Xiang Li, Qibin Hou, Ming-Ming Cheng |
| 2025 | CVPR | KAC: Kolmogorov-Arnold Classifier for Continual Learning. | Yusong Hu, Zichen Liang, Fei Yang, Qibin Hou, Xialei Liu, Ming-Ming Cheng |
| 2025 | CVPR | GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery. | Enguang Wang, Zhimao Peng, Zhengyuan Xie, Fei Yang, Xialei Liu, Ming-Ming Cheng |
| 2025 | ICCV | Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning. | Linlan Huang, Xusheng Cao, Haori Lu, Yifan Meng, Fei Yang, Xialei Liu |
| 2024 | AAAI | Fine-Grained Knowledge Selection and Restoration for Non-exemplar Class Incremental Learning. | Jiang-Tian Zhai, Xialei Liu, Lu Yu, Ming-Ming Cheng |
| 2024 | CVPR | Generative Multi-modal Models are Good Class-Incremental Learners. | Xusheng Cao, Haori Lu, Linlan Huang, Xialei Liu, Ming-Ming Cheng |
| 2024 | CVPR | Task-Adaptive Saliency Guidance for Exemplar-Free Class Incremental Learning. | Xialei Liu, Jiang-Tian Zhai, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng |
| 2024 | ECCV | Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion. | Linlan Huang, Xusheng Cao, Haori Lu, Xialei Liu |
| 2024 | ECCV | Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation. | Zhengyuan Xie, Haiquan Lu, Jia-Wen Xiao, Enguang Wang, Le Zhang, Xialei Liu |
| 2024 | IJCAI | Let's Start Over: Retraining with Selective Samples for Generalized Category Discovery. | Zhimao Peng, Enguang Wang, Xialei Liu, Ming-Ming Cheng |
| 2023 | CVPR | Endpoints Weight Fusion for Class Incremental Semantic Segmentation. | Jia-Wen Xiao, Chang-Bin Zhang, Jiekang Feng, Xialei Liu, Joost van de Weijer, Ming-Ming Cheng |
| 2023 | ICCV | Lighting Every Darkness in Two Pairs : A Calibration-Free Pipeline for RAW Denoising. | Xin Jin, Jia-Wen Xiao, Linghao Han, Chunle Guo, Ruixun Zhang, Xialei Liu, Chongyi Li |
| 2023 | ICCV | Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. | Yuyang Liu, Yang Cong, Dipam Goswami, Xialei Liu, Joost van de Weijer |
| 2023 | ICCV | Masked Autoencoders are Efficient Class Incremental Learners. | Jiang-Tian Zhai, Xialei Liu, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng |
| 2022 | BMVC | Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. | Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer |
| 2022 | CVPR | Cross-domain Few-shot Learning with Task-specific Adapters. | Wei-Hong Li, Xialei Liu, Hakan Bilen |
| 2022 | CVPR | Learning Multiple Dense Prediction Tasks from Partially Annotated Data. | Wei-Hong Li, Xialei Liu, Hakan Bilen |
| 2022 | CVPR | Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. | Kai Wang, Xialei Liu, Andy Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer |
| 2022 | CVPR | Representation Compensation Networks for Continual Semantic Segmentation. | Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng |
| 2022 | ECCV | Long-Tailed Class Incremental Learning. | Xialei Liu, Yusong Hu, Xu-Sheng Cao, Andrew D. Bagdanov, Ke Li, Ming-Ming Cheng |
| 2021 | BMVC | HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. | Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer |
| 2021 | ICCV | Universal Representation Learning from Multiple Domains for Few-shot Classification. | Wei-Hong Li, Xialei Liu, Hakan Bilen |
| 2020 | CVPR | Semantic Drift Compensation for Class-Incremental Learning. | Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer |
| 2020 | CVPR | Generative Feature Replay For Class-Incremental Learning. | Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer |
| 2020 | ICPR | Learning to Rank for Active Learning: A Listwise Approach. | Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu |
| 2019 | CVPR | Learning Metrics From Teachers: Compact Networks for Image Embedding. | Lu Yu, Vacit Oguz Yazici, Xialei Liu, Joost van de Weijer, Yongmei Cheng, Arnau Ramisa |
| 2018 | CVPR | Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. | Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov |
| 2018 | ICPR | Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting. | Xialei Liu, Marc Masana, Luis Herranz, Joost van de Weijer, Antonio M. Lpez, Andrew D. Bagdanov |
| 2017 | ICCV | RankIQA: Learning from Rankings for No-Reference Image Quality Assessment. | Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov |
| 2015 | ISKE | Suitability of Real-Time Image under Complicated Environment Based on Contourlet in SMN. | Lu Yu, Yongmei Cheng, Xialei Liu, Nan Liu |