| Class-incremental learning: survey and performance evaluation on image classification M Masana, X Liu, B Twardowski, M Menta, AD Bagdanov, J van de Weijer IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (5), 2023 | 841 | 2023 |
| Rankiqa: Learning from rankings for no-reference image quality assessment X Liu, J van de Weijer, AD Bagdanov International Conference on Computer Vision (ICCV), 2017, 2017 | 567 | 2017 |
| Memory Replay GANs: learning to generate images from new categories without forgetting C Wu, L Herranz, X Liu, Y Wang, J van de Weijer, B Raducanu Thirty-second Conference on Neural Information Processing Systems (NIPS), 2018, 2018 | 512* | 2018 |
| Semantic Drift Compensation for Class-Incremental Learning L Yu, B Twardowski, X Liu, L Herranz, K Wang, Y Cheng, S Jui, ... Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 380 | 2020 |
| Leveraging Unlabeled Data for Crowd Counting by Learning to Rank X Liu, J van de Weijer, AD Bagdanov Computer Vision and Pattern Recognition (CVPR), 2018, 2018 | 338 | 2018 |
| Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting X Liu, M Masana, L Herranz, J Van de Weijer, AM Lopez, AD Bagdanov International Conference on Pattern Recognition (ICPR), 2018, Oral, 2018 | 334 | 2018 |
| Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank X Liu, J van de Weijer, AD Bagdanov IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 | 217 | 2019 |
| Generative feature replay for class-incremental learning X Liu, C Wu, M Menta, L Herranz, B Raducanu, AD Bagdanov, S Jui, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 180 | 2020 |
| Learning Metrics from Teachers: Compact Networks for Image Embedding L Yu, VO Yazici, X Liu, J van de Weijer, Y Cheng, A Ramisa Computer Vision and Pattern Recognition (CVPR), 2019, 2019 | 155 | 2019 |
| Cross-domain Few-shot Learning with Task-specific Adapters WH Li, X Liu, H Bilen IEEE/CVF Conference on Computer Vision and Pattern Recognition, 7161-7170, 2022 | 147 | 2022 |
| Representation Compensation Networks for Continual Semantic Segmentation CB Zhang, JW Xiao, X Liu, YC Chen, MM Cheng Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 120 | 2022 |
| Universal Representation Learning from Multiple Domains for Few-shot Classification WH Li, X Liu, H Bilen International Conference on Computer Vision (ICCV), 2021, 2021 | 116 | 2021 |
| Self-training for class-incremental semantic segmentation L Yu, X Liu, J Van de Weijer IEEE Transactions on Neural Networks and Learning Systems, 2022 | 66 | 2022 |
| Multi-Task Incremental Learning for Object Detection X Liu, H Yang, A Ravichandran, R Bhotika, S Soatto arXiv preprint arXiv:2002.05347, 2020 | 58* | 2020 |
| Endpoints Weight Fusion for Class Incremental Semantic Segmentation JW Xiao, CB Zhang, J Feng, X Liu, J van de Weijer, MM Cheng Computer Vision and Pattern Recognition (CVPR), 2023, 7204-7213, 2023 | 52 | 2023 |
| Long-Tailed Class Incremental Learning X Liu, YS Hu, XS Cao, AD Bagdanov, K Li, MM Cheng ECCV, 2022, 2022 | 47 | 2022 |
| Learning Multiple Dense Prediction Tasks from Partially Annotated Data WH Li, X Liu, H Bilen Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 41 | 2022 |
| Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection L Yuyang, C Yang, G Dipam, L Xialei, J van de Weijer ICCV 2023, 2023 | 31* | 2023 |
| Learning to Rank for Active Learning: A Listwise Approach M Li, X Liu, J van de Weijer, B Raducanu International Conference on Pattern Recognition (ICPR), 2020, Oral, 2020 | 27 | 2020 |
| Universal Representations: A Unified Look at Multiple Task and Domain Learning WH Li, X Liu, H Bilen IJCV, 2023 | 26 | 2023 |
Joost van de WeijerComputer Vision Center, Universitat Autònoma de Barcelona在 cvc.uab.es 的电子邮件经过验证