iCaRL: Incremental Classifier and Representation Learning

Cited by (1,014)

Items 201–300 of 1,014

1. Online Continual Learning with Maximally Interfered Retrieval
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2. Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-Organization
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3. Knowledge distillation for incremental learning in semantic segmentation
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4. DASO: Distribution-Aware Semantics-Oriented Pseudo-label for Imbalanced Semi-Supervised Learning
   Youngtaek Oh, Dong-Jin Kim, In So Kweon · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
5. More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning
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6. Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers
   Romil Bhardwaj, Zhengxu Xia, Ganesh Ananthanarayanan, Junchen Jiang, Nikolaos Karianakis, Yuanchao Shu, Kevin Hsieh, Victor Bahl, Ion Gabriel Stoica · 2020 · arXiv (Cornell University)
7. Integrative Few-Shot Learning for Classification and Segmentation
   Dahyun Kang, Minsu Cho · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
8. A TinyML Platform for On-Device Continual Learning With Quantized Latent Replays
   Leonardo Ravaglia, Manuele Rusci, D. Nadalini, Alessandro Capotondi, Francesco Conti, L. Benini · 2021 · IEEE Journal on Emerging and Selected Topics in Circuits and Systems
9. Revisiting Open World Object Detection
   Xiaowei Zhao, Yuqing Ma, Duorui Wang, Yifan Shen, Yixuan Qiao, Xianglong Liu · 2023 · IEEE Transactions on Circuits and Systems for Video Technology
10. Functional Regularisation for Continual Learning with Gaussian Processes
    Michalis K. Titsias, Jonathan Schwarz, Alexander Matthews, Razvan Pascanu, Yee Whye Teh · 2019 · arXiv (Cornell University)
11. Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima
    Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu · 2021 · arXiv (Cornell University)
12. Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting
    Craig Atkinson, Brendan Mccane A, Lech Szymanski, Anthony V. Robins · 2020 · Neurocomputing
13. Incorporating neuro-inspired adaptability for continual learning in artificial intelligence
    Wang, Liyuan, Zhang, Xingxing, Li, Qian, Zhang, Mingtian, Su, Hang, Zhu, Jun, Zhong, Yi · 2023 · Nature Machine Intelligence
14. Bearing fault diagnosis under various conditions using an incremental learning-based multi-task shared classifier
    Pengcheng Wang, Hui Xiong, Haoxiang He · 2023 · Knowledge-Based Systems
15. A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
    Zhenyi Wang, Enneng Yang, Li Shen, Heng Huang · 2024 · IEEE Transactions on Pattern Analysis and Machine Intelligence
16. Learning to Segment the Tail
    Xinting Hu, Yi Jiang, Kaihua Tang, Jingyuan Chen, Chunyan Miao, Hanwang Zhang · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
17. Uncertainty-Aware Contrastive Distillation for Incremental Semantic Segmentation
    Guanglei Yang, Enrico Fini, Dan Xu, Paolo Rota, Mingli Ding, Moin Nabi, Xavier Alameda-Pineda, Elisa Ricci · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
18. TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation
    Jie Zhang, Chen Chen, Weiming Zhuang, Lingjuan Lyu · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
19. Toward Training Recurrent Neural Networks for Lifelong Learning
    Shagun Sodhani, Sarath Chandar, Yoshua Bengio · 2019 · Neural Computation
20. GraphSAIL
    Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates · 2020 · ACM International Conference on Information and Knowledge Management (CIKM)
21. Continual Learning of Large Language Models: A Comprehensive Survey
    Haizhou Shi, Zihao Xu, Hengyi Wang, Weiyi Qin, Wenyuan Wang, Yibin Wang, Zifeng Wang, Sayna Ebrahimi, Hao Wang · 2025 · ACM Computing Surveys
22. Improved Distribution Matching for Dataset Condensation
    Ganlong Zhao, Guanbin Li, Yipeng Qin, Yizhou Yu · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
23. Synaptic metaplasticity in binarized neural networks
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24. Few-Shot Class-Incremental Learning for System-Level Fault Diagnosis of Wind Turbine
    Shen Yan, Haidong Shao, Xudong Wang, Jie Wang · 2024 · IEEE/ASME Transactions on Mechatronics
25. DualNet: Continual Learning, Fast and Slow
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26. LIQA: Lifelong Blind Image Quality Assessment
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27. Co-Transport for Class-Incremental Learning
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28. Incremental Object Detection via Meta-Learning
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29. A Few-Shot Class-Incremental Learning Method for Network Intrusion Detection
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30. Superposition of many models into one
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31. Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning
    Wenke Huang, Mang Ye, Zekun Shi, Bo Du · 2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence
32. Automatic Industry PCB Board DIP Process Defect Detection System Based on Deep Ensemble Self-Adaption Method
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33. R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning
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34. UC-OWOD: Unknown-Classified Open World Object Detection
    Zhiheng Wu, Yue Lu, Xingyu Chen, Zhengxing Wu, Liwen Kang, Junzhi Yu · 2022 · Lecture notes in computer science
35. Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation
    Chenyu You, Jinlin Xiang, Kun Su, Xiaoran Zhang, Siyuan Dong, John A. Onofrey, Lawrence H. Staib, James S. Duncan · 2022 · Lecture notes in computer science
36. The Computational and Neural Bases of Context-Dependent Learning
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37. Memory Replay GANs: learning to generate images from new categories without forgetting
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38. Dynamic Support Network for Few-Shot Class Incremental Learning
    Boyu Yang, Mingbao Lin, Yunxiao Zhang, Binghao Liu, Xiaodan Liang, Rongrong Ji, Qixiang Ye · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
39. Efficient Low-Resolution Face Recognition via Bridge Distillation
    Shiming Ge, Shengwei Zhao, Chenyu Li, Yu Zhang, Jia Li · 2020 · IEEE Transactions on Image Processing
40. ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning
    Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
41. Rehearsal revealed: The limits and merits of revisiting samples in continual learning
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42. Deep Metric Learning for Open World Semantic Segmentation
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43. GAN Memory with No Forgetting
    Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin · 2020 · arXiv (Cornell University)
44. Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference
    Menelaos Kanakis, David Brüggemann, Suman Saha, Stamatios Georgoulis, Anton Obukhov, Luc Van Gool · 2020 · Lecture notes in computer science
45. Class Incremental Learning With Few-Shots Based on Linear Programming for Hyperspectral Image Classification
    Jing Bai, Anran Yuan, Zhu Qiang Xiao, Huaji Zhou, Dingchen Wang, Hongbo Jiang, Licheng Jiao · 2020 · IEEE Transactions on Cybernetics
46. Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning
    Riccardo Volpi, Diane Larlus, Grégory Rogez · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
47. Condensing Graphs via One-Step Gradient Matching
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48. A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation
    Dhairyya Singh, Kenneth A. Norman, Anna C. Schapiro · 2022 · Proceedings of the National Academy of Sciences
49. Class-Incremental Exemplar Compression for Class-Incremental Learning
    Zilin Luo, Yaoyao Liu, Bernt Schiele, Qianru Sun · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
50. No One Left Behind: Real-World Federated Class-Incremental Learning
    Jiahua Dong, Hongliu Li, Yang Cong, Gan Sun, Yulun Zhang, Luc Van Gool · 2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence
51. Few-Shot Class-Incremental Learning for Classification and Object Detection: A Survey
    Zhang, Jinghua, Liu, Li, Silvén, Olli, Pietikäinen, Matti, Hu, Dewen · 2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
52. ScaIL: Classifier Weights Scaling for Class Incremental Learning
    Eden Belouadah, Adrian Popescu · 2020 · IEEE Winter Conference on Applications of Computer Vision
53. Towards Backward-Compatible Representation Learning
    Yantao Shen, Yuanjun Xiong, Wei Xia, Stefano Soatto · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
54. MetaSearch: Incremental Product Search via Deep Meta-Learning
    Qi Wang, Xinchen Liu, Wu Liu, An-An Liu, Wenyin Liu, Tao Mei · 2020 · IEEE Transactions on Image Processing
55. Multiple Trajectory Prediction of Moving Agents With Memory Augmented Networks
    Francesco Marchetti, Federico Becattini, Lorenzo Seidenari, Alberto Del Bimbo · 2020 · IEEE Transactions on Pattern Analysis and Machine Intelligence
56. Continual Learning for Text Classification with Information Disentanglement Based Regularization
    Huang, Yufan, Zhang, Yanzhe, Chen, Jiaao, Wang, Xuezhi, Yang, Diyi · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
57. Continual learning of neural networks for quality prediction in production using memory aware synapses and weight transfer
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58. Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting
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59. Continual Object Detection: A review of definitions, strategies, and challenges
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60. GKEAL: Gaussian Kernel Embedded Analytic Learning for Few-Shot Class Incremental Task
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61. Dense Network Expansion for Class Incremental Learning
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62. Class-Incremental Learning with Strong Pre-trained Models
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63. Continual Image Deraining With Hypergraph Convolutional Networks
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64. Continual Deep Learning by Functional Regularisation of Memorable Past
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65. Towards retraining-free RNA modification prediction with incremental learning
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66. A new feature boosting based continual learning method for bearing fault diagnosis with incremental fault types
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67. OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning
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68. Multi-View correlation distillation for incremental object detection
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69. Continual learning for predictive maintenance: Overview and challenges
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70. On the Stability-Plasticity Dilemma of Class-Incremental Learning
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71. Continual Learning: A Review of Techniques, Challenges, and Future Directions
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72. Lifelong Zero-Shot Learning
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73. Self-Training for Class-Incremental Semantic Segmentation
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74. Decoding Imagined Speech Based on Deep Metric Learning for Intuitive BCI Communication
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75. Synthesized Feature based Few-Shot Class-Incremental Learning on a Mixture of Subspaces
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76. Model Behavior Preserving for Class-Incremental Learning
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77. Continual Learning with Lifelong Vision Transformer
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78. Applications of Federated Learning in Mobile Health: Scoping Review
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79. DREAM: Efficient Dataset Distillation by Representative Matching
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80. Robust Few-Shot Learning for User-Provided Data
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81. Layerwise Optimization by Gradient Decomposition for Continual Learning
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82. A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials
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83. Memorizing Complementation Network for Few-Shot Class-Incremental Learning
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84. Auto-encoding and Distilling Scene Graphs for Image Captioning
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85. Task Adaptive Parameter Sharing for Multi-Task Learning
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86. Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation
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87. Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning
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88. Graph Lifelong Learning: A Survey
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89. Online Prototype Learning for Online Continual Learning
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90. An unknown wafer surface defect detection approach based on Incremental Learning for reliability analysis
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91. Measuring and regularizing networks in function space
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92. SpaceNet: Make Free Space for Continual Learning
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93. Untitled work
    2021 · International Conference on Learning Representations
94. Learning to Classify With Incremental New Class
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95. An Efficient Domain-Incremental Learning Approach to Drive in All Weather Conditions
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96. Efficient Parametrization of Multi-domain Deep Neural Networks
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97. Continual learning in sensor-based human activity recognition: An empirical benchmark analysis
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98. Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector
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99. Federated Learning Empowered Real-Time Medical Data Processing Method for Smart Healthcare
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100. Efficient Feature Transformations for Discriminative and Generative Continual Learning
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