Topology-Preserving Class-Incremental Learning

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474 · see citing works

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155 · see citing works

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333 · see citing works

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 56,035 · see citing works

You Only Look Once: Unified, Real-Time Object Detection

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803 · see citing works

Fully convolutional networks for semantic segmentation

Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834 · see citing works

Learning Multiple Layers of Features from Tiny Images

Krizhevsky, A. (2024) · doi:10.57702/zp44cu3g · Cited by 23,890 · see citing works

Distilling the Knowledge in a Neural Network

Hinton, G., Vinyals, O., & Dean, J. (2015) · arXiv · doi:10.48550/arxiv.1503.02531 · Cited by 14,204 · see citing works

Overcoming catastrophic forgetting in neural networks

Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1611835114 · Cited by 7,899 · see citing works

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

Deng, J., Guo, J., Xue, N., & Zafeiriou, S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00482 · Cited by 7,781 · see citing works

Learning without Forgetting

Li, Z., & Hoiem, D. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2773081 · Cited by 4,202 · see citing works

iCaRL: Incremental Classifier and Representation Learning

Rebuffi, S.-A., Kolesnikov, A., Sperl, G., & Lampert, C. H. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.587 · Cited by 3,988 · see citing works

SphereFace: Deep Hypersphere Embedding for Face Recognition

Liu, W., Wen, Y., Yu, Z., Li, M., Raj, B., & Song, L. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.713 · Cited by 3,128 · see citing works

Continual lifelong learning with neural networks: A review

Parisi, G. I., Kemker, R., Part, J. L., Kanan, C., & Wermter, S. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.01.012 · Cited by 3,117 · see citing works

Catastrophic forgetting in connectionist networks

French, R. (1999) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(99)01294-2 · Cited by 2,311 · see citing works

Continual Learning Through Synaptic Intelligence

Zenke, F., Poole, B., & Ganguli, S. (2017) · arXiv · doi:10.48550/arxiv.1703.04200 · Cited by 1,784 · see citing works

Relational Knowledge Distillation

Park, W., Kim, D., Lu, Y., & Cho, M. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00409 · Cited by 1,783 · see citing works

A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning

Yim, J., Joo, D., Bae, J., & Kim, J. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.754 · Cited by 1,635 · see citing works

Memory Aware Synapses: Learning What (not) to Forget

Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M., & Tuytelaars, T. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01219-9_9 · Cited by 1,590 · see citing works

Gradient Episodic Memory for Continual Learning

Lopez-Paz, D., & Ranzato, M. (2017) · arXiv · doi:10.48550/arxiv.1706.08840 · Cited by 1,403 · see citing works

Continual Learning with Deep Generative Replay

Shin, H., Lee, J. K., Kim, J., & Kim, J. (2017) · arXiv · doi:10.48550/arxiv.1705.08690 · Cited by 1,385 · see citing works

Large Scale Incremental Learning

Wu, Y., Chen, Y., Wang, L., Ye, Y., Liu, Z., Guo, Y., & Fu, Y. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00046 · Cited by 1,313 · see citing works

PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

Mallya, A., & Lazebnik, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00810 · Cited by 1,258 · see citing works

Rethinking the Value of Network PruningPreprint

Liu, Z., Sun, M., Zhou, T., Huang, G. M., & Darrell, T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1810.05270 · Cited by 1,225 · see citing works

Learning a Unified Classifier Incrementally via Rebalancing

Hou, S., Pan, X., Loy, C. C., Wang, Z., & Lin, D. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00092 · Cited by 1,195 · see citing works

End-to-End Incremental Learning

Castro, F. M., Marín-Jiménez, M. J., Guil, N., Schmid, C., & Alahari, K. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01258-8_15 · Cited by 1,184 · see citing works

Topology representing networks

Martinetz, T., & Schulten, K. (1994) · Neural Networks · doi:10.1016/0893-6080(94)90109-0 · Cited by 879 · see citing works

Untitled work

(2006) · doi:10.7551/mitpress/7503.003.0029 · Cited by 753 · see citing works

Bayesian Loss for Crowd Count Estimation With Point Supervision

Ma, Z., Wei, X., Hong, X., & Gong, Y. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00624 · Cited by 668 · see citing works

Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Mallya, A., Davis, D., & Lazebnik, S. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01225-0_5 · Cited by 644 · see citing works

Few-Shot Class-Incremental Learning

Tao, X., Hong, X., Chang, X., Dong, S., Wei, X., & Gong, Y. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01220 · Cited by 499 · see citing works

Overcoming Catastrophic Forgetting by Incremental Moment MatchingPreprint

Lee, S.-W., Kim, J.-H., Jun, J., Ha, J.-W., & Zhang, B. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1703.08475 · Cited by 472 · see citing works

Continuous learning in single-incremental-task scenarios

Maltoni, D., & Lomonaco, V. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.03.010 · Cited by 309 · see citing works

IL2M: Class Incremental Learning With Dual Memory

Belouadah, E., & Popescu, A. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00067 · Cited by 302 · see citing works

The topological approach to perceptual organization

Chen, L. (2005) · Visual Cognition · doi:10.1080/13506280444000256 · Cited by 262 · see citing works

Competitive Hebbian Learning Rule Forms Perfectly Topology Preserving Maps

Martinetz, T. (1993) · ICANN ’93 · doi:10.1007/978-1-4471-2063-6_104 · Cited by 256 · see citing works

COMPETITIVE HEBBIAN LEARNING RULE FORMS PERFECTLY TOPOLOGY PRESERVING MAPS

Martinez, T. M. B. (1993) · Cited by 228 · see citing works

Lifelong GAN: Continual Learning for Conditional Image Generation

Zhai, M., Chen, L., Tung, F., He, J., Nawhal, M., & Mori, G. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00285 · Cited by 186 · see citing works

Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification

Wei, X., Zhang, Y., Gong, Y., Zhang, J., & Zheng, N. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01219-9_22 · Cited by 99 · see citing works

The thermal signature of a submerged jet impacting normal to a free surface

Judd, K. P., Savelyev, I., Zhang, Q., & Handler, R. (2015) · Journal of Visualization · doi:10.1007/s12650-015-0303-0 · Cited by 83 · see citing works

Kernelized Subspace Pooling for Deep Local Descriptors

Wei, X., Zhang, Y., Gong, Y., & Zheng, N. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00200 · Cited by 42 · see citing works

Bi-Objective Continual Learning: Learning ‘New’ While Consolidating ‘Known’

Tao, X., Hong, X., Chang, X., & Gong, Y. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i04.6060 · Cited by 29 · see citing works

Visual working memory representation as a topological defined perceptual object

Wei, N., Zhou, T., Zhang, Z., Zhuo, Y., & Chen, L. (2019) · Journal of Vision · doi:10.1167/19.7.12 · Cited by 26 · see citing works

Cogradient Descent for Bilinear Optimization

Zhuo, L., Zhang, B., Yang, L., Chen, H., Ye, Q., Doermann, D., Ji, R., & Guo, G. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00798 · Cited by 14 · see citing works

Graph-based Knowledge Distillation by Multi-head Self-attention Network

Lee, S. H., & Song, B. C. (2019) · Cited by 10 · see citing works

DER: Dynamically Expandable Representation for Class Incremental Learning

Yan, S., Xie, J., & He, X. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00303 · Cited by 752 · see citing works

Online continual learning in image classification: An empirical survey

Mai, Z., Li, R., Jeong, J., Quispe, D., Kim, H., & Sanner, S. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.10.021 · Cited by 422 · see citing works

Class-Incremental Learning: A Survey

Zhou, D.-W., Wang, Q.-W., Qi, Z.-H., Ye, H.-J., Zhan, D.-C., & Liu, Z. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3429383 · Cited by 376 · see citing works

Adaptive Aggregation Networks for Class-Incremental Learning

Liu, Y., Schiele, B., & Sun, Q. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00257 · Cited by 245 · see citing works

Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning

Zhu, K., Cao, Y. H., Zhai, W., Cheng, J., & Zha, Z.-J. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00673 · Cited by 185 · see citing works

Distilling Causal Effect of Data in Class-Incremental Learning

Hu, X., Tang, K., Miao, C., Hua, X., & Zhang, H. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00395 · Cited by 198 · see citing works

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks

Zhou, D.-W., Ye, H.-J., Ma, L., Xie, D., Pu, S., & Zhan, D.-C. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3200865 · Cited by 168 · see citing works

Few-Shot Class-Incremental Learning via Relation Knowledge Distillation

Dong, S., Hong, X., Tao, X., Chang, X., Wei, X., & Gong, Y. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i2.16213 · Cited by 161 · see citing works

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning

Zhou, D.-W., Sun, H., Ye, H.-J., & Zhan, D. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02223 · Cited by 131 · see citing works

Representation Compensation Networks for Continual Semantic Segmentation

Zhang, C., Xiao, J.-W., Liu, X., Chen, Y.-C., & Cheng, M. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00692 · Cited by 126 · see citing works

MgSvF: Multi-Grained Slow versus Fast Framework for Few-Shot Class-Incremental Learning

Zhao, H., Fu, Y., Kang, M., Tian, Q., Wu, F., & Li, X. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3133897 · Cited by 115 · see citing works

Essentials for Class Incremental Learning

Mittal, S., Galesso, S., & Brox, T. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00390 · Cited by 110 · see citing works

Replay in Deep Learning: Current Approaches and Missing Biological Elements

Hayes, T. L., Krishnan, G. P., Bazhenov, M., Siegelmann, H. T., Sejnowski, T. J., & Kanan, C. (2021) · Neural Computation · doi:10.1162/neco_a_01433 · Cited by 106 · see citing works

Continual Detection Transformer for Incremental Object Detection

Liu, Y., Schiele, B., Vedaldi, A., & Rupprecht, C. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.02279 · Cited by 100 · see citing works

Few-Shot Learning With a Strong Teacher

Ye, H.-J., Lu, M., Zhan, D., & Chao, W. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3160362 · Cited by 82 · see citing works

ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning

Wang, L., Yang, K., Li, C., Hong, L., Li, Z., & Zhu, J. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00534 · Cited by 81 · see citing works

Class-Incremental Learning with Strong Pre-trained Models

Wu, T.-Y., Gurumurthy, S., Li, Z., Ravichandran, A., Vasconcelos, N. M., Bhotika, R., & Soatto, S. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00938 · Cited by 73 · see citing works

Multi-View correlation distillation for incremental object detection

Yang, D., Zhou, Y., Zhang, A., Sun, X., Wu, D., Wang, W., & Ye, Q. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108863 · Cited by 70 · see citing works

Model Behavior Preserving for Class-Incremental Learning

Liu, Y., Hong, X., Tao, X., Dong, S., Shi, J., & Gong, Y. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3144183 · Cited by 69 · see citing works

Layerwise Optimization by Gradient Decomposition for Continual Learning

Tang, S., Chen, D., Zhu, J., Yu, S., & Ouyang, W. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00951 · Cited by 67 · see citing works

A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials

Li, C., Huang, Z., Paudel, D. P., Wang, Y., Shahbazi, M., Hong, X., & Gool, L. V. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00139 · Cited by 69 · see citing works

Untitled work

(2021) · International Conference on Learning Representations · Cited by 65 · see citing works

Continuous transfer of neural network representational similarity for incremental learning

Tian, S., Li, W., Ning, X., Ran, H., Qin, H., & Tiwari, P. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126300 · Cited by 63 · see citing works

Continual Learning With Knowledge Distillation: A Survey

Li, S., Su, T., Zhang, X.-Y., & Wang, Z. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3476068 · Cited by 63 · see citing works

Learning Without Forgetting for Vision-Language Models

Zhou, D.-W., Zhang, Y., Wang, Y., Ning, J., Ye, H.-J., Zhan, D., & Liu, Z. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3540889 · Cited by 71 · see citing works

Semantic Knowledge Guided Class-Incremental Learning

Wang, S., Shi, W., Dong, S., Gao, X., Song, X. R., & Gong, Y. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3262739 · Cited by 55 · see citing works

Isolation and Impartial Aggregation: A Paradigm of Incremental Learning without Interference

Wang, Y., Ma, Z., Huang, Z., Wang, Y., Su, Z., & Hong, X. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i8.26216 · Cited by 55 · see citing works

Class-Incremental Learning using Diffusion Model for Distillation and Replay

Jodelet, Q., Liu, X., Phua, Y. J., & Murata, T. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00367 · Cited by 48 · see citing works

Defense Against Adversarial Attacks Using Topology Aligning Adversarial Training

Kuang, H., Liu, H., Lin, X., & Ji, R. (2024) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2024.3359820 · Cited by 46 · see citing works

Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning

Yan, Q., Gong, D., Liu, Y., van den Hengel, A., & Shi, Q. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00021 · Cited by 42 · see citing works

DER: Dynamically Expandable Representation for Class Incremental LearningPreprint

Yan, S., Xie, J., & He, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.16788 · Cited by 41 · see citing works

Patch-based Knowledge Distillation for Lifelong Person Re-Identification

Sun, Z., & Mu, Y. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548179 · Cited by 40 · see citing works

General Incremental Learning with Domain-aware Categorical Representations

Xie, J., Yan, S., & He, X. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01395 · Cited by 40 · see citing works

Knowledge aggregation networks for class incremental learning

Fu, Z., Wang, Z., Xu, X., Li, D., & Yang, H. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109310 · Cited by 39 · see citing works

Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data

Tang, Y.-M., Peng, Y.-X., & Zheng, W. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00933 · Cited by 39 · see citing works

CKDF: Cascaded Knowledge Distillation Framework for Robust Incremental Learning

Li, K., Wan, J., & Yu, S. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3176130 · Cited by 36 · see citing works

Augmented Geometric Distillation for Data-Free Incremental Person ReID

Lu, Y., Wang, M., & Deng, W. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00718 · Cited by 36 · see citing works

Online Hyperparameter Optimization for Class-Incremental Learning

Liu, Y., Li, Y., Schiele, B., & Sun, Q. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i7.26070 · Cited by 36 · see citing works

Analogical Learning-Based Few-Shot Class-Incremental Learning

Li, J., Dong, S., Gong, Y., He, Y., & Wei, X. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3350913 · Cited by 30 · see citing works

Semantics-Driven Generative Replay for Few-Shot Class Incremental Learning

Agarwal, A., Banerjee, B., Fabio Cuzzolin, A., & Chaudhuri, S. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548160 · Cited by 29 · see citing works

Overcoming Catastrophic Forgetting for Multi-Label Class-Incremental Learning

Song, X. R., Shu, K., Dong, S., Cheng, J., Wei, X., & Gong, Y. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00238 · Cited by 28 · see citing works

Knowledge-Preserving continual person re-identification using Graph Attention Network

Liu, Z., Feng, C., Chen, S., & Hu, J. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.01.033 · Cited by 25 · see citing works

Class-Incremental Learning Method With Fast Update and High Retainability Based on Broad Learning System

Du, J., Liu, P., Vong, C., Chen, C., Wang, T., & Chen, C. L. P. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3259016 · Cited by 24 · see citing works

Heterogeneous Forgetting Compensation for Class-Incremental Learning

Dong, J.-H., Liang, W., Yang, C., & Sun, G. (2023) · IEEE International Conference on Computer Vision · doi:10.1109/iccv51070.2023.01078 · Cited by 32 · see citing works

When Video Classification Meets Incremental Classes

Zhao, H., Qin, X., Su, S., Fu, Y., Lin, Z., & Li, X. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3475265 · Cited by 26 · see citing works

Multi-feature space similarity supplement for few-shot class incremental learning

Xu, X., Niu, S., Wang, Z., Guo, W., Jing, L., & Yang, H. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110394 · Cited by 24 · see citing works

Mine-Distill-Prototypes for Complete Few-Shot Class-Incremental Learning in Image Classification

Tai, Y., Tan, Y., Xiong, S., & Tian, J. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3248601 · Cited by 23 · see citing works

Domain Incremental Object Detection Based on Feature Space Topology Preserving Strategy

Ding, L., Song, X. R., He, Y., Wang, C., Dong, S., Wei, X., & Gong, Y. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3285263 · Cited by 22 · see citing works

Language-Inspired Relation Transfer for Few-Shot Class-Incremental Learning

Zhao, Y., Li, J., Song, Z., & Tian, Y. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3492328 · Cited by 22 · see citing works

Generalized Knowledge Distillation via Relationship Matching

Ye, H.-J., Lu, S., & Zhan, D. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3160328 · Cited by 24 · see citing works

Balanced softmax cross-entropy for incremental learning with and without memory

Jodelet, Q., Liu, X., & Murata, T. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103582 · Cited by 23 · see citing works

Balanced Softmax Cross-Entropy for Incremental Learning

Jodelet, Q., Liu, X., & Murata, T. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86340-1_31 · Cited by 21 · see citing works

Non-exemplar Domain Incremental Object Detection via Learning Domain Bias

Song, X. R., He, Y., Dong, S., & Gong, Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i13.29427 · Cited by 20 · see citing works

Continual learning in medical image analysis: A survey

Wu, X., Xu, Z., & Tong, R. K. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.109206 · Cited by 22 · see citing works

Evolving Parameterized Prompt Memory for Continual Learning

Kurniawan, M. R., Song, X. R., Ma, Z., He, Y., Gong, Y., Qi, Y., & Wei, X. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i12.29231 · Cited by 20 · see citing works

Energy-Based Models for Continual LearningPreprint

Li, S., Du, Y., van de Ven, G. M., & Mordatch, I. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.12216 · Cited by 19 · see citing works

Deep Class-Incremental Learning From Decentralized Data

Zhang, X., Dong, S., Chen, J., Tian, Q. C., Gong, Y., & Hong, X. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3214573 · Cited by 16 · see citing works

Distilling Causal Effect of Data in Class-Incremental LearningPreprint

Hu, X., Tang, K., Miao, C., Hua, X., & Zhang, H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.01737 · Cited by 16 · see citing works

SSGCN: a sampling sequential guided graph convolutional network

Wang, X., Yang, X., Wang, P., Yu, H., & Xu, T. (2023) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-023-02013-2 · Cited by 15 · see citing works

MoBoo: Memory-Boosted Vision Transformer for Class-Incremental Learning

Ni, B., Nie, X., Zhang, C., Xu, S., Zhang, X., Meng, G., & Xiang, S. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3417431 · Cited by 16 · see citing works

Enhancing Visual Continual Learning with Language-Guided Supervision

Ni, B., Zhao, H., Zhang, C., Hu, K., Meng, G., Zhang, Z., & Xiang, S. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02272 · Cited by 15 · see citing works

Beyond Prompt Learning: Continual Adapter for Efficient Rehearsal-Free Continual Learning

Gao, X., Dong, S., He, Y., Wang, Q., & Gong, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73013-9_6 · Cited by 15 · see citing works

Selective Replay Enhances Learning in Online Continual Analogical Reasoning

Hayes, T. L., & Kanan, C. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00389 · Cited by 16 · see citing works

Kohonen Self-Organizing Map based Route Planning: A Revisit

Guan, Q., Hong, X., Ke, W., Zhang, L., Sun, G., & Gong, Y. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636025 · Cited by 14 · see citing works

Few Shot Class Incremental Learning via Efficient Prototype Replay and Calibration

Zhang, W., & Gu, X. (2023) · Entropy · doi:10.3390/e25050776 · Cited by 14 · see citing works

Incremental learning for an evolving stream of medical ultrasound images via counterfactual thinking

Gao, J., Xu, L., & Wan, M. (2023) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2023.102290 · Cited by 14 · see citing works

FoCL: Feature-oriented continual learning for generative models

Lao, Q., Mortazavi, M., Tahaei, M. S., Dutil, F., Fevens, T., & Havaei, M. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108127 · Cited by 14 · see citing works

Rehearsal-Free and Efficient Continual Learning for Cross-Domain Face Anti-Spoofing

Cai, R., Cui, Y., Yu, Z., Lin, X., Chen, C., & Kot, A. C. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3601053 · Cited by 13 · see citing works

Coarse-To-Fine Incremental Few-Shot Learning

Xiang, X., Tan, Y., Wan, Q., Ma, J., Yuille, A., & Hager, G. D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19821-2_12 · Cited by 15 · see citing works

Knowledge Restore and Transfer for Multi-Label Class-Incremental Learning

Dong, S., Luo, H., He, Y., Wei, X., Cheng, J., & Gong, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01715 · Cited by 13 · see citing works

A Class-Incremental Learning Method for SAR Images Based on Self-Sustainment Guidance Representation

Pan, Q., Liao, K., He, X., Bu, Z., & Huang, J. (2023) · Remote Sensing · doi:10.3390/rs15102631 · Cited by 12 · see citing works

Non-Exemplar Class-Incremental Learning via Adaptive Old Class Reconstruction

Wang, S., Shi, W., He, Y., Yu, Y., & Gong, Y. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611926 · Cited by 12 · see citing works

Balanced Destruction-Reconstruction Dynamics for Memory-Replay Class Incremental Learning

Zhou, Y., Yao, J., Hong, F., Zhang, Y., & Wang, Y. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3451932 · Cited by 13 · see citing works

DYSON: Dynamic Feature Space Self-Organization for Online Task-Free Class Incremental Learning

He, Y., Chen, Y., Jin, Y., Dong, S., Wei, X., & Gong, Y. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02241 · Cited by 12 · see citing works

CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning

Dong, S., Gao, X., He, Y., Zhou, Z., Kot, A. C., & Gong, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3502837 · Cited by 13 · see citing works

Incorporating geometry knowledge into an incremental learning structure for few-shot intent recognition

Zhang, X., Jiang, M., Chen, H., Zheng, J., & Pan, Z. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.109296 · Cited by 11 · see citing works

Dual Compensation Residual Networks for Class Imbalanced Learning

Hou, R., Chang, H., Ma, B., Shan, S., & Chen, X. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3275585 · Cited by 11 · see citing works

Leveraging Old Knowledge to Continually Learn New Classes in Medical Images

Chee, E. Y. L., Lee, M. L., & Hsu, W. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i12.26659 · Cited by 11 · see citing works

Hyper-feature aggregation and relaxed distillation for class incremental learning

Wu, R., Liu, H., Yue, Z., Li, J., & Sham, C. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110440 · Cited by 11 · see citing works

Interactive Continual Learning Architecture for Long-Term Personalization of Home Service Robots

Ayub, A., Nehaniv, C. L., & Dautenhahn, K. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611386 · Cited by 11 · see citing works

APM: Adaptive parameter multiplexing for class incremental learning

Gao, J., Xie, T., Li, R., Wang, K., & Zhao, L.-J. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125135 · Cited by 11 · see citing works

Federated Incremental Learning algorithm based on Topological Data Analysis

Hu, K., Gong, S., Li, L., Luo, Y., Luo, Y., Jiang, S., & Xia, M. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111048 · Cited by 11 · see citing works

CMoA: Contrastive Mixture of Adapters for Generalized Few-Shot Continual Learning

Cui, Y., Zhao, J. C., Yu, Z., Cai, R., Wang, X., Jin, L., Kot, A. C., Liu, L., & Li, X. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3543038 · Cited by 11 · see citing works

PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental Learning

Zhu, F., Zhang, X.-Y., Cheng, Z., & Liu, C. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3568886 · Cited by 11 · see citing works

Cross-Class Feature Augmentation for Class Incremental Learning

Kim, T., Park, J., & Han, B. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i12.29216 · Cited by 12 · see citing works

Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos

Liu, Y., Li, Y., Schiele, B., & Sun, Q. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00222 · Cited by 9 · see citing works

Hierarchical Augmentation and Distillation for Class Incremental Audio-Visual Video Recognition

Zuo, Y., Yao, H., Zhuang, L., & Xu, C. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3387946 · Cited by 9 · see citing works

Reshaping the Online Data Buffering and Organizing Mechanism for Continual Test-Time Adaptation

Zhu, Z., Hong, X., Ma, Z., Zhuang, W., Ma, Y., Dai, Y., & Wang, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73007-8_24 · Cited by 9 · see citing works

Continual Learning Through Human-Robot Interaction: Human Perceptions of a Continual Learning Robot in Repeated Interactions

Ayub, A., Francesco, Z. D., Holthaus, P., Nehaniv, C. L., & Dautenhahn, K. (2025) · International Journal of Social Robotics · doi:10.1007/s12369-025-01214-9 · Cited by 12 · see citing works

Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation

Deng, P., Zhang, J., Sheng, X., Yan, C. C., Sun, Y., Fu, Y., & Li, L. (2025) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52734.2025.02846 · Cited by 8 · see citing works

Continual Recognition with Adaptive Memory Update

Yao, X., Wang, X. Y., Liu, Y., & Zhu, W. (2022) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3573202 · Cited by 8 · see citing works

Evidential Deep Learning for Class-Incremental Semantic Segmentation

Holmquist, K., Klasen, L. M., & Felsberg, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-31438-4_3 · Cited by 8 · see citing works

Class Incremental Learning based on Identically Distributed Parallel One-Class Classifiers

Sun, W., Li, Q., Zhang, J., Wang, W., & Geng, Y. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126579 · Cited by 8 · see citing works

Incremental Model Enhancement via Memory-based Contrastive Learning

Xuan, S., Yang, M., & Zhang, S. S. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02138-z · Cited by 8 · see citing works

Class Incremental Learning for Video Action Classification

Ma, J., Tao, X., Ma, J., Hong, X., & Gong, Y. (2021) · Proceedings - International Conference on Image Processing · doi:10.1109/icip42928.2021.9506788 · Cited by 8 · see citing works

UnDAF: A General Unsupervised Domain Adaptation Framework for Disparity or Optical Flow Estimation

Wang, H., Fan, R., Cai, P., Liu, M., & Wang, L. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9811811 · Cited by 8 · see citing works

Multi-Centroid Task Descriptor for Dynamic Class Incremental Inference

Cai, T., Zhang, Z., Tan, X., Qu, Y., Jiang, G., Wang, C., & Xie, Y. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00705 · Cited by 7 · see citing works

Preparing the Future for Continual Semantic Segmentation

Lin, Z., Wang, Z., & Zhang, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01094 · Cited by 7 · see citing works

G-DriverAUT: A Growable Driver Authentication Scheme Based on Incremental Learning

Xun, Y., Guo, W., & Liu, J. (2023) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2022.3233739 · Cited by 7 · see citing works

Leveraging joint incremental learning objective with data ensemble for class incremental learning

Mazumder, P., Karim, M. A., Joshi, I., & Singh, P. P. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.01.017 · Cited by 7 · see citing works

Topology-aware Knowledge Preservation for Class-Incremental Learning

Zang, H., Dong, Y., Li, L., Yang, L., & Wang, Y. (2026) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v40i33.40031

Dynamic Topology-Preserving Multi-Label Class-Incremental Learning

Shi, W., & Xu, Y. (2026) · Symmetry · doi:10.3390/sym18101666

Class-Incremental Learning with Topological Schemas of Memory Spaces

Chang, X., Tao, X., Hong, X., Wei, X., Ke, W., & Gong, Y. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412125 · Cited by 3 · see citing works

Few-Shot Class-Incremental LearningPreprint

Tao, X., Hong, X., Chang, X., Dong, S., Wei, X., & Gong, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.10956 · Cited by 14 · see citing works

Class-Incremental Learning with Rectified Feature-Graph Preservation

Lei, C.-H., Chen, Y.-H., Peng, W.-H., & Chiu, W.-C. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69544-6_22 · Cited by 5 · see citing works