Xialei Liu

Int. J. Comput. Vis., May, 2024

Modeling Inner- and Cross-Task Contrastive Relations for Continual Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2024

GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery.

[BibT_eX]

[DOI]

CoRR, 2024

A<sup>3</sup>R: Vision Language Pre-training by Attentive Alignment and Attentive Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition and Computer Vision - 7th Chinese Conference, 2024

Let's Start Over: Retraining with Selective Samples for Generalized Category Discovery.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

Task-Adaptive Saliency Guidance for Exemplar-Free Class Incremental Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Generative Multi-modal Models are Good Class-Incremental Learners.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Fine-Grained Knowledge Selection and Restoration for Non-exemplar Class Incremental Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Sequential interactive image segmentation.

[BibT_eX]

[DOI]

Comput. Vis. Media, December, 2023

Self-Training for Class-Incremental Semantic Segmentation.

[BibT_eX]

[DOI]

Lu Yu

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Class-Incremental Learning: Survey and Performance Evaluation on Image Classification.

[BibT_eX]

[DOI]

Marc Masana

Bartlomiej Twardowski

Mikel Menta

IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Class Incremental Learning with Pre-trained Vision-Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Masked Autoencoders are Efficient Class Incremental Learners.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Lighting Every Darkness in Two Pairs : A Calibration-Free Pipeline for RAW Denoising.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Endpoints Weight Fusion for Class Incremental Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Robust Saliency Guidance for Data-free Class Incremental Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Long-Tailed Class Incremental Learning.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Representation Compensation Networks for Continual Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Learning Multiple Dense Prediction Tasks from Partially Annotated Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Cross-domain Few-shot Learning with Task-specific Adapters.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification.

[BibT_eX]

[DOI]

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Improving Task Adaptation for Cross-domain Few-shot Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Universal Representation Learning from Multiple Domains for Few-shot Classification.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification.

[BibT_eX]

[DOI]

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Class-incremental learning: survey and performance evaluation.

[BibT_eX]

[DOI]

Marc Masana

Bartlomiej Twardowski

Mikel Menta

CoRR, 2020

Continual Universal Object Detection.

[BibT_eX]

[DOI]

CoRR, 2020

Learning to Rank for Active Learning: A Listwise Approach.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Generative Feature Replay For Class-Incremental Learning.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Semantic Drift Compensation for Class-Incremental Learning.

[BibT_eX]

[DOI]

Lu Yu

Bartlomiej Twardowski

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Visual recognition in the wild: learning from rankings in small domains and continual learning in new domains.

[BibT_eX]

[DOI]

PhD thesis, 2019

Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Learning Metrics From Teachers: Compact Networks for Image Embedding.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Memory Replay GANs: learning to generate images from new categories without forgetting.

[BibT_eX]

[DOI]

CoRR, 2018

Memory Replay GANs: Learning to Generate New Categories without Forgetting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Leveraging Unlabeled Data for Crowd Counting by Learning to Rank.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

RankIQA: Learning from Rankings for No-Reference Image Quality Assessment.

[BibT_eX]

[DOI]