Suitability of Real-Time Image under Complicated Environment Based on Contourlet in SMN. - Lu Yu 004; Yongmei Cheng; Xialei Liu; Nan Liu (ISKE, 2015)

RankIQA: Learning from Rankings for No-Reference Image Quality Assessment. - Xialei Liu; Joost van de Weijer 001; Andrew D. Bagdanov (ICCV, 2017)

Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. - Xialei Liu; Joost van de Weijer 001; Andrew D. Bagdanov (CVPR, 2018)

Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting. - Xialei Liu; Marc Masana; Luis Herranz; Joost van de Weijer 001; Antonio M. López 001; Andrew D. Bagdanov (ICPR, 2018)

Memory Replay GANs: Learning to Generate New Categories without Forgetting. - Chenshen Wu; Luis Herranz; Xialei Liu; Yaxing Wang; Joost van de Weijer 001; Bogdan Raducanu (NeurIPS, 2018)

Memory Replay GANs: learning to generate images from new categories without forgetting. - Chenshen Wu; Luis Herranz; Xialei Liu; Yaxing Wang; Joost van de Weijer 001; Bogdan Raducanu (CoRR, 2018)

Learning Metrics From Teachers: Compact Networks for Image Embedding. - Lu Yu 004; Vacit Oguz Yazici; Xialei Liu; Joost van de Weijer 001; Yongmei Cheng; Arnau Ramisa (CVPR, 2019)

Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank. - Xialei Liu; Joost van de Weijer 001; Andrew D. Bagdanov (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Visual recognition in the wild: learning from rankings in small domains and continual learning in new domains. - Xialei Liu (2019)

Semantic Drift Compensation for Class-Incremental Learning. - Lu Yu 004; Bartlomiej Twardowski; Xialei Liu; Luis Herranz; Kai Wang 060; Yongmei Cheng; Shangling Jui; Joost van de Weijer 001 (CVPR, 2020)

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 001 (CVPR Workshops, 2020)

Learning to Rank for Active Learning: A Listwise Approach. - Minghan Li 003; Xialei Liu; Joost van de Weijer 001; Bogdan Raducanu (ICPR, 2020)

Continual Universal Object Detection. - Xialei Liu; Hao Yang 043; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (CoRR, 2020)

Class-incremental learning: survey and performance evaluation. - Marc Masana; Xialei Liu; Bartlomiej Twardowski; Mikel Menta; Andrew D. Bagdanov; Joost van de Weijer 001 (CoRR, 2020)

HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. - Kai Wang 060; Xialei Liu; Luis Herranz; Joost van de Weijer 001 (BMVC, 2021)

Universal Representation Learning from Multiple Domains for Few-shot Classification. - Wei-Hong Li; Xialei Liu; Hakan Bilen (ICCV, 2021)

Improving Task Adaptation for Cross-domain Few-shot Learning. - Wei-Hong Li; Xialei Liu; Hakan Bilen (CoRR, 2021)

Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. - Kai Wang 060; Chenshen Wu; Andy Bagdanov; Xialei Liu; Shiqi Yang; Shangling Jui; Joost van de Weijer 001 (BMVC, 2022)

Cross-domain Few-shot Learning with Task-specific Adapters. - Wei-Hong Li; Xialei Liu; Hakan Bilen (CVPR, 2022)

Learning Multiple Dense Prediction Tasks from Partially Annotated Data. - Wei-Hong Li; Xialei Liu; Hakan Bilen (CVPR, 2022)

Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. - Kai Wang 060; Xialei Liu; Andy Bagdanov; Luis Herranz; Shangling Jui; Joost van de Weijer 001 (CVPR Workshops, 2022)

Representation Compensation Networks for Continual Semantic Segmentation. - Chang-Bin Zhang; Jia-Wen Xiao; Xialei Liu; Ying-Cong Chen; Ming-Ming Cheng (CVPR, 2022)

Long-Tailed Class Incremental Learning. - Xialei Liu; Yusong Hu; Xu-Sheng Cao; Andrew D. Bagdanov; Ke Li; Ming-Ming Cheng (ECCV (33), 2022)

Robust Saliency Guidance for Data-free Class Incremental Learning. - Xialei Liu; Jiang-Tian Zhai; Andrew D. Bagdanov; Ke Li; Ming-Ming Cheng (CoRR, 2022)

Endpoints Weight Fusion for Class Incremental Semantic Segmentation. - Jia-Wen Xiao; Chang-Bin Zhang; Jiekang Feng; Xialei Liu; Joost van de Weijer 001; Ming-Ming Cheng (CVPR, 2023)

Lighting Every Darkness in Two Pairs : A Calibration-Free Pipeline for RAW Denoising. - Xin Jin 005; Jia-Wen Xiao; Linghao Han; Chunle Guo; Ruixun Zhang; Xialei Liu; Chongyi Li (ICCV, 2023)

Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. - Yuyang Liu; Yang Cong; Dipam Goswami; Xialei Liu; Joost van de Weijer 001 (ICCV, 2023)

Masked Autoencoders are Efficient Class Incremental Learners. - Jiang-Tian Zhai; Xialei Liu; Andrew D. Bagdanov; Ke Li; Ming-Ming Cheng (ICCV, 2023)

Class Incremental Learning with Pre-trained Vision-Language Models. - Xialei Liu; Xusheng Cao; Haori Lu; Jia-Wen Xiao; Andrew D. Bagdanov; Ming-Ming Cheng (CoRR, 2023)

Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. - Marc Masana; Xialei Liu; Bartlomiej Twardowski; Mikel Menta; Andrew D. Bagdanov; Joost van de Weijer 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Self-Training for Class-Incremental Semantic Segmentation. - Lu Yu 004; Xialei Liu; Joost van de Weijer 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Sequential interactive image segmentation. - Zheng Lin 005; Zhao Zhang 018; Ziyue Zhu; Deng-Ping Fan; Xialei Liu (Comput. Vis. Media, 2023)

Fine-Grained Knowledge Selection and Restoration for Non-exemplar Class Incremental Learning. - Jiang-Tian Zhai; Xialei Liu; Lu Yu 004; Ming-Ming Cheng (AAAI, 2024)

Generative Multi-modal Models are Good Class-Incremental Learners. - Xusheng Cao; Haori Lu; Linlan Huang; Xialei Liu; Ming-Ming Cheng (CVPR, 2024)

Task-Adaptive Saliency Guidance for Exemplar-Free Class Incremental Learning. - Xialei Liu; Jiang-Tian Zhai; Andrew D. Bagdanov; Ke Li; Ming-Ming Cheng (CVPR, 2024)

Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion. - Linlan Huang; Xusheng Cao; Haori Lu; Xialei Liu (ECCV (54), 2024)

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 (ECCV (26), 2024)

Let's Start Over: Retraining with Selective Samples for Generalized Category Discovery. - Zhimao Peng; Enguang Wang; Xialei Liu; Ming-Ming Cheng (IJCAI, 2024)

A3R: Vision Language Pre-training by Attentive Alignment and Attentive Reconstruction. - Yusong Hu; Yuting Gao; Zihan Xu; Ke Li 015; Xialei Liu (PRCV (5), 2024)

GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery. - Enguang Wang; Zhimao Peng; Zhengyuan Xie; Xialei Liu; Ming-Ming Cheng (CoRR, 2024)

Modeling Inner- and Cross-Task Contrastive Relations for Continual Image Classification. - Yuxuan Luo; Runmin Cong; Xialei Liu; Horace Ho-Shing Ip; Sam Kwong (IEEE Trans. Multim., 2024)

Universal Representations: A Unified Look at Multiple Task and Domain Learning. - Wei-Hong Li; Xialei Liu; Hakan Bilen (Int. J. Comput. Vis., 2024)

KAC: Kolmogorov-Arnold Classifier for Continual Learning. - Yusong Hu; Zichen Liang; Fei Yang; Qibin Hou; Xialei Liu; Ming-Ming Cheng (CVPR, 2025)

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 (CVPR, 2025)

Enhancing Continual Semantic Segmentation via Uncertainty and Class Balance Re-Weighting. - Zichen Liang; Yusong Hu; Fei Yang 004; Xialei Liu (IEEE Trans. Image Process., 2025)

Class Incremental Learning for Image Classification With Out-of-Distribution Task Identification. - Xusheng Cao; Haori Lu; Xialei Liu; Ming-Ming Cheng (IEEE Trans. Multim., 2025)

Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection. - Xinbin Yuan; Zhaohui Zheng 003; Yuxuan Li 004; Xialei Liu; Li Liu 004; Xiang Li 041; Qibin Hou; Ming-Ming Cheng (CoRR, 2025)

Reformulating Classification as Image-Class Matching for Class Incremental Learning. - Yusong Hu; Zichen Liang; Xialei Liu; Qibin Hou; Ming-Ming Cheng (IEEE Trans. Circuits Syst. Video Technol., 2025)

Learning Part Knowledge to Facilitate Category Understanding for Fine-Grained Generalized Category Discovery. - Enguang Wang; Zhimao Peng; Zhengyuan Xie; Haori Lu; Fei Yang; Xialei Liu (CoRR, 2025)

Restoring Forgotten Knowledge in Non-Exemplar Class Incremental Learning through Test-Time Semantic Evolution. - Haori Lu; Xusheng Cao; Linlan Huang; Enguang Wang; Fei Yang; Xialei Liu (CoRR, 2025)

Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning. - Xusheng Cao; Haori Lu; Linlan Huang; Fei Yang; Xialei Liu; Ming-Ming Cheng (CoRR, 2025)

Predictive Sample Assignment for Semantically Coherent Out-of-Distribution Detection. - Zhimao Peng; Enguang Wang; Xialei Liu; Ming-Ming Cheng (IEEE Trans. Circuits Syst. Video Technol., 2025)

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 (CoRR, 2025)

Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting. - Yuyang Liu; Qiuhe Hong; Linlan Huang; Alexandra Gomez-Villa; Dipam Goswami; Xialei Liu; Joost van de Weijer 001; Yonghong Tian 001 (CoRR, 2025)