14.2.6.1.1 Continual Learning

Chapter Contents (Back)
Continual Learning.
See also Dynamic Learning, Incremental Learning.

Wang, K.[Kai], van de Weijer, J.[Joost], Herranz, L.[Luis],
ACAE-REMIND for online continual learning with compressed feature replay,
PRL(150), 2021, pp. 122-129.
Elsevier DOI 2109
online continual learning, autoencoders, vector quantization BibRef

Lomonaco, V.[Vincenzo], Pellegrini, L.[Lorenzo], Rodriguez, P.[Pau], Caccia, M.[Massimo], She, Q.[Qi], Chen, Y.[Yu], Jodelet, Q.[Quentin], Wang, R.P.[Rui-Ping], Mai, Z.[Zheda], Vazquez, D.[David], Parisi, G.I.[German I.], Churamani, N.[Nikhil], Pickett, M.[Marc], Laradji, I.[Issam], Maltoni, D.[Davide],
CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions,
AI(303), 2022, pp. 103635.
Elsevier DOI 2201
Continual learning, Lifelong learning, Incremental learning, Challenge BibRef

de Lange, M.[Matthias], Aljundi, R.[Rahaf], Masana, M.[Marc], Parisot, S.[Sarah], Jia, X.[Xu], Leonardis, A.[Aleš], Slabaugh, G.[Gregory], Tuytelaars, T.[Tinne],
A Continual Learning Survey: Defying Forgetting in Classification Tasks,
PAMI(44), No. 7, July 2022, pp. 3366-3385.
IEEE DOI 2206
Survey, Continual Learning. Task analysis, Knowledge engineering, Neural networks, Training, Training data, Learning systems, Interference, Continual learning, neural networks BibRef

Lan, C.L.[Chuan-Lin], Feng, F.[Fan], Liu, Q.[Qi], She, Q.[Qi], Yang, Q.[Qihan], Hao, X.Y.[Xin-Yue], Mashkin, I.[Ivan], Kei, K.S.[Ka Shun], Qiang, D.[Dong], Lomonaco, V.[Vincenzo], Shi, X.S.[Xue-Song], Wang, Z.W.[Zheng-Wei], Guo, Y.[Yao], Zhang, Y.M.[Yi-Min], Qiao, F.[Fei], Chan, R.H.M.[Rosa H.M.],
Towards lifelong object recognition: A dataset and benchmark,
PR(130), 2022, pp. 108819.
Elsevier DOI 2206
Robotic vision, Continual learning, Lifelong learning, Object recognition BibRef

Xu, J.[Ju], Ma, J.[Jin], Gao, X.S.[Xue-Song], Zhu, Z.X.[Zhan-Xing],
Adaptive Progressive Continual Learning,
PAMI(44), No. 10, October 2022, pp. 6715-6728.
IEEE DOI 2209
Task analysis, Optimization, Bayes methods, Training, Reinforcement learning, Knowledge engineering, Complexity theory, neural networks BibRef

Zhuang, C.[Chen], Huang, S.L.[Shao-Li], Cheng, G.[Gong], Ning, J.F.[Ji-Feng],
Multi-criteria Selection of Rehearsal Samples for Continual Learning,
PR(132), 2022, pp. 108907.
Elsevier DOI 2209
Continual Learning, Multiple Criteria, Rehersal Method, Learning to learn BibRef

Zhao, X.Y.[Xing-Yu], An, Y.X.[Yue-Xuan], Xu, N.[Ning], Geng, X.[Xin],
Continuous label distribution learning,
PR(133), 2023, pp. 109056.
Elsevier DOI 2210
Label distribution learning, Continuous label distribution, Label ambiguity, Label encoding, Label correlations BibRef

Jodelet, Q.[Quentin], Liu, X.[Xin], Murata, T.[Tsuyoshi],
Balanced softmax cross-entropy for incremental learning with and without memory,
CVIU(225), 2022, pp. 103582.
Elsevier DOI 2212
Continual learning, Class incremental learning, Image classification, Bias mitigation BibRef

Thuseethan, S.[Selvarajah], Rajasegarar, S.[Sutharshan], Yearwood, J.[John],
Deep Continual Learning for Emerging Emotion Recognition,
MultMed(24), 2022, pp. 4367-4380.
IEEE DOI 2212
Emotion recognition, Task analysis, Feature extraction, Learning systems, Transfer learning, Training, Databases, unknown emotions BibRef

Ji, Z.[Zhong], Li, J.[Jin], Wang, Q.[Qiang], Zhang, Z.F.[Zhong-Fei],
Complementary Calibration: Boosting General Continual Learning With Collaborative Distillation and Self-Supervision,
IP(32), 2023, pp. 657-667.
IEEE DOI 2301
Task analysis, Feature extraction, Calibration, Collaboration, Training, Testing, Ear, General continual learning, supervised contrastive learning BibRef

Zamorski, M.[Maciej], Stypulkowski, M.[Michal], Karanowski, K.[Konrad], Trzcinski, T.[Tomasz], Zieba, M.[Maciej],
Continual learning on 3D point clouds with random compressed rehearsal,
CVIU(228), 2023, pp. 103621.
Elsevier DOI 2302
Continual learning, Point cloud, Deep learning, Data compression BibRef

Zhang, X.[Xikun], Song, D.J.[Dong-Jin], Tao, D.C.[Da-Cheng],
Hierarchical Prototype Networks for Continual Graph Representation Learning,
PAMI(45), No. 4, April 2023, pp. 4622-4636.
IEEE DOI 2303
Task analysis, Prototypes, Feature extraction, Memory management, Knowledge engineering, Representation learning, graph neural networks BibRef

Knowledge engineering, Interference, Continual learning, replay methods

Hu, H.[Hexiang], Sener, O.[Ozan], Sha, F.[Fei], Koltun, V.[Vladlen],
Drinking From a Firehose: Continual Learning With Web-Scale Natural Language,
PAMI(45), No. 5, May 2023, pp. 5684-5696.
IEEE DOI 2304
Task analysis, Benchmark testing, Learning systems, Multitasking, Social networking (online), Neural networks, Data models, web-scale datasets BibRef

Kong, Y.J.[Ya-Jing], Liu, L.[Liu], Qiao, M.Y.[Mao-Ying], Wang, Z.[Zhen], Tao, D.C.[Da-Cheng],
Trust-Region Adaptive Frequency for Online Continual Learning,
IJCV(131), No. 7, July 2023, pp. 1825-1839.
Springer DOI 2307
BibRef

Li, D.P.[De-Peng], Zeng, Z.G.[Zhi-Gang],
CRNet: A Fast Continual Learning Framework With Random Theory,
PAMI(45), No. 9, September 2023, pp. 10731-10744.
IEEE DOI 2309
BibRef

Li, X.R.[Xiao-Rong], Wang, S.P.[Shi-Peng], Sun, J.[Jian], Xu, Z.B.[Zong-Ben],
Variational Data-Free Knowledge Distillation for Continual Learning,
PAMI(45), No. 10, October 2023, pp. 12618-12634.
IEEE DOI 2310
BibRef
Earlier: A2, A1, A3, A4:
Training Networks in Null Space of Feature Covariance for Continual Learning,
CVPR21(184-193)
IEEE DOI 2111
Training, Null space, Benchmark testing, Approximation algorithms, Stability analysis, Pattern recognition BibRef

Li, X.R.[Xiao-Rong], Wang, S.P.[Shi-Peng], Sun, J.[Jian], Xu, Z.B.[Zong-Ben],
Memory efficient data-free distillation for continual learning,
PR(144), 2023, pp. 109875.
Elsevier DOI 2310
Continual learning, Catastrophic forgetting, Knowledge distillation BibRef

Wang, Z.Y.[Zhen-Yi], Shen, L.[Li], Duan, T.[Tiehang], Suo, Q.L.[Qiu-Ling], Fang, L.[Le], Liu, W.[Wei], Gao, M.C.[Ming-Chen],
Distributionally Robust Memory Evolution With Generalized Divergence for Continual Learning,
PAMI(45), No. 12, December 2023, pp. 14337-14352.
IEEE DOI 2311
BibRef

Pham, Q.[Quang], Liu, C.H.[Cheng-Hao], Hoi, S.C.H.[Steven C. H.],
Continual Learning, Fast and Slow,
PAMI(46), No. 1, January 2024, pp. 134-149.
IEEE DOI 2312
BibRef

Jeong, S.[Seungwoo], Ko, W.J.[Won-Jun], Mulyadi, A.W.[Ahmad Wisnu], Suk, H.I.[Heung-Il],
Deep Efficient Continuous Manifold Learning for Time Series Modeling,
PAMI(46), No. 1, January 2024, pp. 171-184.
IEEE DOI 2312
BibRef

Yu, D.[Da], Zhang, M.Y.[Ming-Yi], Li, M.T.[Man-Tian], Zha, F.S.[Fu-Sheng], Zhang, J.[Junge], Sun, L.[Lining], Huang, K.Q.[Kai-Qi],
Contrastive Correlation Preserving Replay for Online Continual Learning,
CirSysVideo(34), No. 1, January 2024, pp. 124-139.
IEEE DOI 2401
BibRef

Mazumder, P.[Pratik], Singh, P.[Pravendra], Rai, P.[Piyush], Namboodiri, V.P.[Vinay P.],
Rectification-Based Knowledge Retention for Task Incremental Learning,
PAMI(46), No. 3, March 2024, pp. 1561-1575.
IEEE DOI 2402
BibRef
Earlier: A2, A1, A3, A4:
Rectification-based Knowledge Retention for Continual Learning,
CVPR21(15277-15286)
IEEE DOI 2111
Task analysis, Training, Testing, Data models, Adaptation models, Training data, Deep learning, Continual learning, deep learning, task incremental learning. Learning systems, Pattern recognition. BibRef

Wang, Y.[Ye], Zhao, G.S.[Guo-Shuai], Qian, X.M.[Xue-Ming],
Improved Continually Evolved Classifiers for Few-Shot Class-Incremental Learning,
CirSysVideo(34), No. 2, February 2024, pp. 1123-1134.
IEEE DOI 2402
Task analysis, Training, Prototypes, Circuit stability, Power capacitors, Measurement, Training data, Lifelong learning, cross-attention mechanism BibRef

Han, Y.N.[Ya-Nan], Liu, J.W.[Jian-Wei],
Adaptive instance similarity embedding for online continual learning,
PR(149), 2024, pp. 110238.
Elsevier DOI 2403
Continual learning, Catastrophic forgetting, Experience replay, Adaptive similarity embedding BibRef

Cong, W.[Wei], Cong, Y.[Yang], Sun, G.[Gan], Liu, Y.Y.[Yu-Yang], Dong, J.H.[Jia-Hua],
Self-Paced Weight Consolidation for Continual Learning,
CirSysVideo(34), No. 4, April 2024, pp. 2209-2222.
IEEE DOI 2404
Task analysis, Heuristic algorithms, Robots, Training, Knowledge based systems, Computational modeling, transfer learning BibRef

Lu, J.X.[Jun-Xin], Sun, S.L.[Shi-Liang],
PAMK: Prototype Augmented Multi-Teacher Knowledge Transfer Network for Continual Zero-Shot Learning,
IP(33), 2024, pp. 3353-3368.
IEEE DOI 2406
Task analysis, Prototypes, Zero-shot learning, Semantics, Training, Knowledge transfer, Continuing education, prototype augmentation BibRef


Lekkala, K.[Kiran], Bhargava, E.[Eshan], Itti, L.[Laurent],
Evaluating Pretrained Models for Deployable Lifelong Learning,
Pretrain24(561-569)
IEEE DOI 2404
Learning systems, Visualization, Scalability, Reinforcement learning, Games BibRef

Tang, C.I.[Chi Ian], Qendro, L.[Lorena], Spathis, D.[Dimitris], Kawsar, F.[Fahim], Mascolo, C.[Cecilia], Mathur, A.[Akhil],
Kaizen: Practical self-supervised continual learning with continual fine-tuning,
WACV24(2829-2838)
IEEE DOI 2404
Training, Measurement, Adaptation models, Computational modeling, Self-supervised learning, Feature extraction, Algorithms, Image recognition and understanding BibRef

Verma, V.[Vinay], Mehta, N.[Nikhil], Liang, K.J.[Kevin J], Mishra, A.[Aakansha], Carin, L.[Lawrence],
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning,
WACV24(2709-2719)
IEEE DOI 2404
Training, Adaptation models, Protocols, Zero-shot learning, Computational modeling, Reservoirs, Data models, Algorithms, Vision + language and/or other modalities BibRef

Yu, X.F.[Xiao-Fan], Rosing, T.[Tajana], Guo, Y.H.[Yun-Hui],
Evolve: Enhancing Unsupervised Continual Learning with Multiple Experts,
WACV24(2355-2366)
IEEE DOI Code:
WWW Link. 2404
Adaptation models, Correlation, Self-supervised learning, Streams, Videos, Algorithms, Machine learning architectures, formulations, and algorithms BibRef

Niloy, F.F.[Fahim Faisal], Ahmed, S.M.[Sk Miraj], Raychaudhuri, D.S.[Dripta S.], Oymak, S.[Samet], Roy-Chowdhury, A.K.[Amit K.],
Effective Restoration of Source Knowledge in Continual Test Time Adaptation,
WACV24(2080-2089)
IEEE DOI 2404
Adaptation models, Estimation, Benchmark testing, Robustness, Faces, Algorithms, Machine learning architectures, formulations, Image recognition and understanding BibRef

Gomez-Villa, A.[Alex], Twardowski, B.[Bartlomiej], Wang, K.[Kai], van de Weijer, J.[Joost],
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning,
WACV24(1679-1689)
IEEE DOI 2404
Knowledge engineering, Representation learning, Self-supervised learning, Task analysis, Algorithms BibRef

Huang, S.K.[Sheng-Kai], Huang, C.R.[Chun-Rong],
Transformer with Task Selection for Continual Learning,
MVA23(1-5)
DOI Link 2403
Machine vision, Transformers, Task analysis, Testing BibRef

Wei, Y.J.[Yu-Jie], Ye, J.X.[Jia-Xin], Huang, Z.Z.[Zhi-Zhong], Zhang, J.P.[Jun-Ping], Shan, H.M.[Hong-Ming],
Online Prototype Learning for Online Continual Learning,
ICCV23(18718-18728)
IEEE DOI Code:
WWW Link. 2401
BibRef

Ge, Y.H.[Yun-Hao], Li, Y.[Yuecheng], Ni, S.[Shuo], Zhao, J.[Jiaping], Yang, M.H.[Ming-Hsuan], Itti, L.[Laurent],
CLR: Channel-wise Lightweight Reprogramming for Continual Learning,
ICCV23(18752-18762)
IEEE DOI 2401
BibRef

Jin, H.[Hyundong], Kim, G.H.[Gyeong-Hyeon], Ahn, C.[Chanho], Kim, E.[Eunwoo],
Growing a Brain with Sparsity-Inducing Generation for Continual Learning,
ICCV23(18915-18924)
IEEE DOI 2401
BibRef

Yang, F.[Fei], Wang, K.[Kai], van de Weijer, J.[Joost],
ScrollNet: Dynamic Weight Importance for Continual Learning,
VCL23(3337-3347)
IEEE DOI 2401
BibRef

Mahmoodi, L.[Leila], Harandi, M.[Mehrtash], Moghadam, P.[Peyman],
Flashback for Continual Learning,
VCL23(3426-3435)
IEEE DOI 2401
BibRef

Khawand, J.[Joe], Hanappe, P.[Peter], Colliaux, D.[David],
Continual Learning with Deep Streaming Regularized Discriminant Analysis,
VCL23(3447-3454)
IEEE DOI 2401
BibRef

Al Kader-Hammoud, H.A.[Hasan Abed], Prabhu, A.[Ameya], Lim, S.N.[Ser-Nam], Torr, P.H.S.[Philip H.S.], Bibi, A.[Adel], Ghanem, B.[Bernard],
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?,
ICCV23(18806-18815)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, E.[Enneng], Shen, L.[Li], Wang, Z.[Zhenyi], Liu, S.W.[Shi-Wei], Guo, G.[Guibing], Wang, X.W.[Xing-Wei],
Data Augmented Flatness-aware Gradient Projection for Continual Learning,
ICCV23(5607-5616)
IEEE DOI 2401
BibRef

Tian, X.D.[Xu-Dong], Zhang, Z.Z.[Zhi-Zhong], Tan, X.[Xin], Liu, J.[Jun], Wang, C.J.[Cheng-Jie], Qu, Y.[Yanyun], Jiang, G.[Guannan], Xie, Y.[Yuan],
Instance and Category Supervision are Alternate Learners for Continual Learning,
ICCV23(5573-5582)
IEEE DOI 2401
BibRef

Wu, Y.[Yanan], Chi, Z.X.[Zhi-Xiang], Wang, Y.[Yang], Feng, S.H.[Song-He],
MetaGCD: Learning to Continually Learn in Generalized Category Discovery,
ICCV23(1655-1665)
IEEE DOI 2401
BibRef

Cheng, H.Y.[Hao-Yang], Wen, H.T.[Hai-Tao], Zhang, X.L.[Xiao-Liang], Qiu, H.Q.[He-Qian], Wang, L.X.[Lan-Xiao], Li, H.L.[Hong-Liang],
Contrastive Continuity on Augmentation Stability Rehearsal for Continual Self-Supervised Learning,
ICCV23(5684-5694)
IEEE DOI 2401
BibRef

Lyu, F.[Fan], Sun, Q.[Qing], Shang, F.[Fanhua], Wan, L.[Liang], Feng, W.[Wei],
Measuring Asymmetric Gradient Discrepancy in Parallel Continual Learning,
ICCV23(11377-11386)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cho, W.[Wonguk], Park, J.[Jinha], Kim, T.[Taesup],
Complementary Domain Adaptation and Generalization for Unsupervised Continual Domain Shift Learning,
ICCV23(11408-11418)
IEEE DOI 2401
BibRef

Khan, M.G.Z.A.[Muhammad Gul Zain Ali], Naeem, M.F.[Muhammad Ferjad], Van Gool, L.J.[Luc J.], Stricker, D.[Didier], Tombari, F.[Federico], Afzal, M.Z.[Muhammad Zeshan],
Introducing Language Guidance in Prompt-based Continual Learning,
ICCV23(11429-11439)
IEEE DOI 2401
BibRef

Gao, Q.[Qiankun], Zhao, C.[Chen], Sun, Y.F.[Yi-Fan], Xi, T.[Teng], Zhang, G.[Gang], Ghanem, B.[Bernard], Zhang, J.[Jian],
A Unified Continual Learning Framework with General Parameter-Efficient Tuning,
ICCV23(11449-11459)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chavan, V.[Vivek], Koch, P.[Paul], Schlüter, M.[Marian], Briese, C.[Clemens],
Towards Realistic Evaluation of Industrial Continual Learning Scenarios with an Emphasis on Energy Consumption and Computational Footprint,
ICCV23(11472-11484)
IEEE DOI 2401
BibRef

Zhang, W.X.[Wen-Xuan], Janson, P.[Paul], Yi, K.[Kai], Skorokhodov, I.[Ivan], Elhoseiny, M.[Mohamed],
Continual Zero-Shot Learning through Semantically Guided Generative Random Walks,
ICCV23(11540-11551)
IEEE DOI Code:
WWW Link. 2401
BibRef

Malepathirana, T.[Tamasha], Senanayake, D.[Damith], Halgamuge, S.[Saman],
NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning,
ICCV23(11640-11650)
IEEE DOI Code:
WWW Link. 2401
BibRef

Singh, P.[Parantak], Li, Y.[You], Sikarwar, A.[Ankur], Lei, W.X.[Wei-Xian], Gao, D.F.[Di-Fei], Talbot, M.B.[Morgan B.], Sun, Y.[Ying], Shou, M.Z.[Mike Zheng], Kreiman, G.[Gabriel], Zhang, M.[Mengmi],
Learning to Learn: How to Continuously Teach Humans and Machines,
ICCV23(11674-11685)
IEEE DOI 2401
BibRef

Lee, B.H.[Byung Hyun], Jung, O.[Okchul], Choi, J.H.[Jong-Hyun], Chun, S.Y.[Se Young],
Online Continual Learning on Hierarchical Label Expansion,
ICCV23(11727-11736)
IEEE DOI 2401
BibRef

Jung, D.[Dahuin], Han, D.Y.[Dong-Yoon], Bang, J.[Jihwan], Song, H.[Hwanjun],
Generating Instance-level Prompts for Rehearsal-free Continual Learning,
ICCV23(11813-11823)
IEEE DOI Code:
WWW Link. 2401
BibRef

Kang, Z.[Zhiqi], Fini, E.[Enrico], Nabi, M.[Moin], Ricci, E.[Elisa], Alahari, K.[Karteek],
A soft nearest-neighbor framework for continual semi-supervised learning,
ICCV23(11834-11843)
IEEE DOI Code:
WWW Link. 2401
BibRef

Rymarczyk, D.[Dawid], van de Weijer, J.[Joost], Zielinski, B.[Bartosz], Twardowski, B.[Bartlomiej],
ICICLE: Interpretable Class Incremental Continual Learning,
ICCV23(1887-1898)
IEEE DOI 2401
BibRef

Pian, W.G.[Wei-Guo], Mo, S.T.[Shen-Tong], Guo, Y.H.[Yun-Hui], Tian, Y.[Yapeng],
Audio-Visual Class-Incremental Learning,
ICCV23(7765-7777)
IEEE DOI Code:
WWW Link. 2401
BibRef

Mo, S.T.[Shen-Tong], Pian, W.G.[Wei-Guo], Tian, Y.P.[Ya-Peng],
Class-Incremental Grouping Network for Continual Audio-Visual Learning,
ICCV23(7754-7764)
IEEE DOI Code:
WWW Link. 2401
BibRef

Hurtado, J.[Julio], Raymond-Sáez, A.[Alain], Araujo, V.[Vladimir], Lomonaco, V.[Vincenzo], Soto, A.[Alvaro], Bacciu, D.[Davide],
Memory Population in Continual Learning via Outlier Elimination,
VCL23(3473-3482)
IEEE DOI 2401
BibRef

Sójka, D.[Damian], Cygert, S.[Sebastian], Twardowski, B.[Bartlomiej], Trzcinski, T.[Tomasz],
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation,
VCL23(3483-3487)
IEEE DOI 2401
BibRef

Khan, V.[Valeriya], Cygert, S.[Sebastian], Twardowski, B.[Bartlomiej], Trzcinski, T.[Tomasz],
Looking through the past: better knowledge retention for generative replay in continual learning,
VCL23(3488-3492)
IEEE DOI 2401
BibRef

Szatkowski, F.[Filip], Pyla, M.[Mateusz], Przewiezlikowski, M.[Marcin], Cygert, S.[Sebastian], Twardowski, B.[Bartlomiej], Trzcinski, T.[Tomasz],
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning,
WACV24(1966-1976)
IEEE DOI 2404
BibRef
Earlier: VCL23(3504-3509)
IEEE DOI 2401
Code:
WWW Link. Training, Adaptation models, Codes, Computational modeling, Source coding, Training data, Benchmark testing, Algorithms, Image recognition and understanding BibRef

Soutif-Cormerais, A.[Albin], Carta, A.[Antonio], Cossu, A.[Andrea], Hurtado, J.[Julio], Lomonaco, V.[Vincenzo], van de Weijer, J.[Joost], Hemati, H.[Hamed],
A Comprehensive Empirical Evaluation on Online Continual Learning,
VCL23(3510-3520)
IEEE DOI Code:
WWW Link. 2401
BibRef

Brignac, D.[Daniel], Lobo, N.[Niels], Mahalanobis, A.[Abhijit],
Improving Replay Sample Selection and Storage for Less Forgetting in Continual Learning,
VCL23(3532-3541)
IEEE DOI 2401
BibRef

Sorrenti, A.[Amelia], Bellitto, G.[Giovanni], Salanitri, F.P.[Federica Proietto], Pennisi, M.[Matteo], Spampinato, C.[Concetto], Palazzo, S.[Simone],
Selective Freezing for Efficient Continual Learning,
VCL23(3542-3551)
IEEE DOI 2401
BibRef

Nagata, K.[Kotaro], Hotta, K.[Kazuhiro],
Margin Contrastive Learning with Learnable-Vector for Continual Learning,
VCL23(3562-3568)
IEEE DOI 2401
BibRef

de Min, T.[Thomas], Mancini, M.[Massimiliano], Alahari, K.[Karteek], Alameda-Pineda, X.[Xavier], Ricci, E.[Elisa],
On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers,
VCL23(3577-3586)
IEEE DOI 2401
BibRef

Wang, Q.Z.[Quan-Ziang], Wang, R.[Renzhen], Wu, Y.C.[Yi-Chen], Jia, X.X.[Xi-Xi], Meng, D.Y.[De-Yu],
CBA: Improving Online Continual Learning via Continual Bias Adaptor,
ICCV23(19036-19046)
IEEE DOI 2401
BibRef

Zheng, Z.W.[Zang-Wei], Ma, M.Y.[Ming-Yuan], Wang, K.[Kai], Qin, Z.H.[Zi-Heng], Yue, X.Y.[Xiang-Yu], You, Y.[Yang],
Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models,
ICCV23(19068-19079)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhang, G.[Gengwei], Wang, L.Y.[Li-Yuan], Kang, G.L.[Guo-Liang], Chen, L.[Ling], Wei, Y.C.[Yun-Chao],
SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model,
ICCV23(19091-19101)
IEEE DOI Code:
WWW Link. 2401
BibRef

Gu, Z.Q.[Zi-Qi], Xu, C.Y.[Chun-Yan], Yang, J.[Jian], Cui, Z.[Zhen],
Few-shot Continual Infomax Learning,
ICCV23(19167-19176)
IEEE DOI 2401
BibRef

Wu, X.H.[Xin-Heng], Lu, J.[Jie], Fang, Z.[Zhen], Zhang, G.Q.[Guang-Quan],
Meta OOD Learning For Continuously Adaptive OOD Detection,
ICCV23(19296-19307)
IEEE DOI 2401
BibRef

Zhang, J.[Jie], Chen, C.[Chen], Zhuang, W.M.[Wei-Ming], Lyu, L.J.[Ling-Juan],
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation,
ICCV23(4759-4770)
IEEE DOI 2401
BibRef

Gan, Y.[Yulu], Pan, M.J.[Ming-Jie], Zhang, R.Y.[Rong-Yu], Ling, Z.J.[Zi-Jian], Zhao, L.[Lingran], Liu, J.M.[Jia-Ming], Zhang, S.H.[Shang-Hang],
Cloud-Device Collaborative Adaptation to Continual Changing Environments in the Real-World,
CVPR23(12157-12166)
IEEE DOI 2309
BibRef

Liu, Z.Z.[Zhi-Zheng], Milano, F.[Francesco], Frey, J.[Jonas], Siegwart, R.[Roland], Blum, H.[Hermann], Cadena, C.[Cesar],
Unsupervised Continual Semantic Adaptation Through Neural Rendering,
CVPR23(3031-3040)
IEEE DOI 2309
BibRef

Döbler, M.[Mario], Marsden, R.A.[Robert A.], Yang, B.[Bin],
Robust Mean Teacher for Continual and Gradual Test-Time Adaptation,
CVPR23(7704-7714)
IEEE DOI 2309
BibRef

Song, J.[Junha], Lee, J.[Jungsoo], Kweon, I.S.[In So], Choi, S.[Sungha],
EcoTTA: Memory-Efficient Continual Test-Time Adaptation via Self-Distilled Regularization,
CVPR23(11920-11929)
IEEE DOI 2309
BibRef

Prasanna, B., Sanyal, S.[Sunandini], Babu, R.V.[R. Venkatesh],
Continual Domain Adaptation through Pruning-aided Domain-specific Weight Modulation,
CLVision23(2457-2463)
IEEE DOI 2309
BibRef

Yuan, L.Q.[Liang-Qi], Ma, Y.S.[Yun-Sheng], Su, L.[Lu], Wang, Z.[Ziran],
Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition,
AICity23(5250-5259)
IEEE DOI 2309
BibRef

Shenaj, D.[Donald], Toldo, M.[Marco], Rigon, A.[Alberto], Zanuttigh, P.[Pietro],
Asynchronous Federated Continual Learning,
FedVision23(5055-5063)
IEEE DOI 2309
BibRef

Chrysakis, A.[Aristotelis], Moens, M.F.[Marie-Francine],
Simulating Task-Free Continual Learning Streams From Existing Datasets,
CLVision23(2516-2524)
IEEE DOI 2309
BibRef

Nazemi, A.[Amir], Moustafa, Z.[Zeyad], Fieguth, P.[Paul],
CLVOS23: A Long Video Object Segmentation Dataset for Continual Learning,
CLVision23(2496-2505)
IEEE DOI 2309
BibRef

Alssum, L.[Lama], Alcázar, J.L.[Juan León], Ramazanova, M.[Merey], Zhao, C.[Chen], Ghanem, B.[Bernard],
Just a Glimpse: Rethinking Temporal Information for Video Continual Learning,
CLVision23(2474-2483)
IEEE DOI 2309
BibRef

Smith, J.S.[James Seale], Tian, J.J.[Jun-Jiao], Halbe, S.[Shaunak], Hsu, Y.C.[Yen-Chang], Kira, Z.[Zsolt],
A Closer Look at Rehearsal-Free Continual Learning *,
CLVision23(2410-2420)
IEEE DOI 2309
BibRef

Harun, M.Y.[Md Yousuf], Gallardo, J.[Jhair], Hayes, T.L.[Tyler L.], Kanan, C.[Christopher],
How Efficient Are Today's Continual Learning Algorithms?,
CLVision23(2431-2436)
IEEE DOI 2309
BibRef

Houyon, J.[Joachim], Cioppa, A.[Anthony], Ghunaim, Y.[Yasir], Alfarra, M.[Motasem], Halin, A.[Anaïs], Henry, M.[Maxim], Ghanem, B.[Bernard], van Droogenbroeck, M.[Marc],
Online Distillation with Continual Learning for Cyclic Domain Shifts,
CLVision23(2437-2446)
IEEE DOI 2309
BibRef

Camuffo, E.[Elena], Milani, S.[Simone],
Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse Data,
CLVision23(2447-2456)
IEEE DOI 2309
BibRef

Wang, Z.Y.[Zhen-Yi], Shen, L.[Li], Zhan, D.L.[Dong-Lin], Suo, Q.L.[Qiu-Ling], Zhu, Y.J.[Yan-Jun], Duan, T.[Tiehang], Gao, M.C.[Ming-Chen],
MetaMix: Towards Corruption-Robust Continual Learning with Temporally Self-Adaptive Data Transformation,
CVPR23(24521-24531)
IEEE DOI 2309
BibRef

Gao, Z.[Zhi], Xu, C.[Chen], Li, F.[Feng], Jia, Y.D.[Yun-De], Harandi, M.[Mehrtash], Wu, Y.W.[Yu-Wei],
Exploring Data Geometry for Continual Learning,
CVPR23(24325-24334)
IEEE DOI 2309
BibRef

Gu, Q.[Qiao], Shim, D.[Dongsub], Shkurti, F.[Florian],
Preserving Linear Separability in Continual Learning by Backward Feature Projection,
CVPR23(24286-24295)
IEEE DOI 2309
BibRef

Lin, H.[Huiwei], Zhang, B.Q.[Bao-Quan], Feng, S.S.[Shan-Shan], Li, X.[Xutao], Ye, Y.M.[Yun-Ming],
PCR: Proxy-Based Contrastive Replay for Online Class-Incremental Continual Learning,
CVPR23(24246-24255)
IEEE DOI 2309
BibRef

Villa, A.[Andrés], Alcázar, J.L.[Juan León], Alfarra, M.[Motasem], Alhamoud, K.[Kumail], Hurtado, J.[Julio], Heilbron, F.C.[Fabian Caba], Soto, A.[Alvaro], Ghanem, B.[Bernard],
PIVOT: Prompting for Video Continual Learning,
CVPR23(24214-24223)
IEEE DOI 2309
BibRef

Sun, Z.C.[Zhi-Cheng], Mu, Y.D.[Ya-Dong], Hua, G.[Gang],
Regularizing Second-Order Influences for Continual Learning,
CVPR23(20166-20175)
IEEE DOI 2309
BibRef

Zhang, X.[Xi], Zhang, F.F.[Fei-Fei], Xu, C.S.[Chang-Sheng],
VQACL: A Novel Visual Question Answering Continual Learning Setting,
CVPR23(19102-19112)
IEEE DOI 2309
BibRef

Nie, X.[Xing], Xu, S.X.[Shi-Xiong], Liu, X.[Xiyan], Meng, G.F.[Gao-Feng], Huo, C.L.[Chun-Lei], Xiang, S.M.[Shi-Ming],
Bilateral Memory Consolidation for Continual Learning,
CVPR23(16026-16035)
IEEE DOI 2309
BibRef

Madaan, D.[Divyam], Yin, H.X.[Hong-Xu], Byeon, W.[Wonmin], Kautz, J.[Jan], Molchanov, P.[Pavlo],
Heterogeneous Continual Learning,
CVPR23(15985-15995)
IEEE DOI 2309
BibRef

Kim, S.[Sanghwan], Noci, L.[Lorenzo], Orvieto, A.[Antonio], Hofmann, T.[Thomas],
Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning,
CVPR23(11930-11939)
IEEE DOI 2309
BibRef

Smith, J.S.[James Seale], Karlinsky, L.[Leonid], Gutta, V.[Vyshnavi], Cascante-Bonilla, P.[Paola], Kim, D.H.[Dong-Hyun], Arbelle, A.[Assaf], Panda, R.[Rameswar], Feris, R.S.[Rogerio S.], Kira, Z.[Zsolt],
CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning,
CVPR23(11909-11919)
IEEE DOI 2309
BibRef

Ghunaim, Y.[Yasir], Bibi, A.[Adel], Alhamoud, K.[Kumail], Alfarra, M.[Motasem], Hammoud, H.A.A.K.[Hasan Abed Al Kader], Prabhu, A.[Ameya], Torr, P.H.S.[Philip H.S.], Ghanem, B.[Bernard],
Real-Time Evaluation in Online Continual Learning: A New Hope,
CVPR23(11888-11897)
IEEE DOI 2309
BibRef

Guo, Y.[Yiduo], Liu, B.[Bing], Zhao, D.Y.[Dong-Yan],
Dealing with Cross-Task Class Discrimination in Online Continual Learning,
CVPR23(11878-11887)
IEEE DOI 2309
BibRef

Liang, Y.S.[Yan-Shuo], Li, W.J.[Wu-Jun],
Adaptive Plasticity Improvement for Continual Learning,
CVPR23(7816-7825)
IEEE DOI 2309
BibRef

Zhao, Z.[Zhen], Zhang, Z.Z.[Zhi-Zhong], Tan, X.[Xin], Liu, J.[Jun], Qu, Y.[Yanyun], Xie, Y.[Yuan], Ma, L.Z.[Li-Zhuang],
Rethinking Gradient Projection Continual Learning: Stability/Plasticity Feature Space Decoupling,
CVPR23(3718-3727)
IEEE DOI 2309
BibRef

Prabhu, A.[Ameya], Hammoud, H.A.A.K.[Hasan Abed Al Kader], Dokania, P.[Puneet], Torr, P.H.S.[Philip H.S.], Lim, S.N.[Ser-Nam], Ghanem, B.[Bernard], Bibi, A.[Adel],
Computationally Budgeted Continual Learning: What Does Matter?,
CVPR23(3698-3707)
IEEE DOI 2309
BibRef

Cermelli, F.[Fabio], Cord, M.[Matthieu], Douillard, A.[Arthur],
CoMFormer: Continual Learning in Semantic and Panoptic Segmentation,
CVPR23(3010-3020)
IEEE DOI 2309
BibRef

Hedegaard, L.[Lukas], Iosifidis, A.[Alexandros],
Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in Pytorch,
CADK22(21-34).
Springer DOI 2304
BibRef

Chandra, D.S.[Dupati Srikar], Varshney, S.[Sakshi], Srijith, P.K., Gupta, S.I.[Sun-Il],
Continual Learning with Dependency Preserving Hypernetworks,
WACV23(2338-2347)
IEEE DOI 2302
Recurrent neural networks, Computational modeling, Task analysis, Image classification, visual reasoning) BibRef

Saha, G.[Gobinda], Roy, K.[Kaushik],
Saliency Guided Experience Packing for Replay in Continual Learning,
WACV23(5262-5272)
IEEE DOI 2302
Location awareness, Learning systems, Visualization, Statistical analysis, Reinforcement learning, visual reasoning) BibRef

Krishnan, R., Balaprakash, P.[Prasanna],
Continual Learning via Dynamic Programming,
ICPR22(1350-1356)
IEEE DOI 2212
Partial differential equations, Benchmark testing, Mathematical models, Dynamic programming, Bellman principle BibRef

Bellitto, G.[Giovanni], Pennisi, M.[Matteo], Palazzo, S.[Simone], Bonicelli, L.[Lorenzo], Boschini, M.[Matteo], Calderara, S.[Simone],
Effects of Auxiliary Knowledge on Continual Learning,
ICPR22(1357-1363)
IEEE DOI 2212
Training, Knowledge engineering, Neural networks, Streaming media, Feature extraction, Data models, Task analysis BibRef

Rios, A.[Amanda], Ahuja, N.[Nilesh], Ndiour, I.[Ibrahima], Genc, U.[Utku], Itti, L.[Laurent], Tickoo, O.[Omesh],
incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection,
ECCV22(XXV:588-604).
Springer DOI 2211
BibRef

He, J.P.[Jiang-Peng], Zhu, F.Q.[Feng-Qing],
Exemplar-Free Online Continual Learning,
ICIP22(541-545)
IEEE DOI 2211
Training, Privacy, Protocols, Benchmark testing, Task analysis, Tuning, Continual learning, Online scenario, Exemplar-free, Image classification BibRef

Michel, N.[Nicolas], Negrel, R.[Romain], Chierchia, G.[Giovanni], Bercher, J.F.[Jean-Fmnçois],
Contrastive Learning for Online Semi-Supervised General Continual Learning,
ICIP22(1896-1900)
IEEE DOI 2211
Training, Memory management, Continual Learning, Contrastive Learning, Semi-Supervised Learning, Memory BibRef

Ye, F.[Fei], Bors, A.G.[Adrian G.],
Wasserstein Expansible Variational Autoencoder for Discriminative and Generative Continual Learning,
ICCV23(18619-18629)
IEEE DOI Code:
WWW Link. 2401
BibRef
And:
Self-Evolved Dynamic Expansion Model for Task-Free Continual Learning,
ICCV23(22045-22055)
IEEE DOI Code:
WWW Link. 2401
BibRef
Earlier:
Learning an Evolved Mixture Model for Task-Free Continual Learning,
ICIP22(1936-1940)
IEEE DOI 2211
Training, Deep learning, Adaptation models, Mixture models, Network architecture, Benchmark testing, Hilbert Schmidt Independence Criterion BibRef

Guimeng, L.[Liu], Yang, G.[Guo], Yin, C.W.S.[Cheryl Wong Sze], Suganathan, P.N.[Ponnuthurai Nagartnam], Savitha, R.[Ramasamy],
Unsupervised Generative Variational Continual Learning,
ICIP22(4028-4032)
IEEE DOI 2211
Training, Adaptation models, Uncertainty, Image coding, Neurons, Benchmark testing, Task analysis, Continual Learning, Unsupervised, Variational Inference BibRef

Findik, Y.[Yasin], Pourkamali-Anaraki, F.[Farhad],
D-CBRS: Accounting for Intra-Class Diversity in Continual Learning,
ICIP22(2531-2535)
IEEE DOI 2211
Memory management, Reservoirs, Data models, Continual learning, lifelong learning, catastrophic forgetting, class-incremental learning BibRef

Pourcel, J.[Julien], Vu, N.S.[Ngoc-Son], French, R.M.[Robert M.],
Online Task-free Continual Learning with Dynamic Sparse Distributed Memory,
ECCV22(XXV:739-756).
Springer DOI 2211
BibRef

Kong, Y.J.[Ya-Jing], Liu, L.[Liu], Wang, Z.[Zhen], Tao, D.C.[Da-Cheng],
Balancing Stability and Plasticity Through Advanced Null Space in Continual Learning,
ECCV22(XXVI:219-236).
Springer DOI 2211
BibRef

Wang, L.Y.[Li-Yuan], Zhang, X.X.[Xing-Xing], Li, Q.[Qian], Zhu, J.[Jun], Zhong, Y.[Yi],
CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One,
ECCV22(XXVI:254-271).
Springer DOI 2211
BibRef

Purushwalkam, S.[Senthil], Morgado, P.[Pedro], Gupta, A.[Abhinav],
The Challenges of Continuous Self-Supervised Learning,
ECCV22(XXVI:702-721).
Springer DOI 2211
BibRef

Li, Z.W.[Zhuo-Wei], Zhao, L.[Long], Zhang, Z.Z.[Zi-Zhao], Zhang, H.[Han], Liu, D.[Di], Liu, T.[Ting], Metaxas, D.N.[Dimitris N.],
Steering Prototypes with Prompt-tuning for Rehearsal-free Continual Learning,
WACV24(2511-2521)
IEEE DOI 2404
Representation learning, Semantics, Prototypes, Interference, Self-supervised learning, Benchmark testing, Algorithms, Image recognition and understanding BibRef

Wang, Z.F.[Zi-Feng], Zhang, Z.Z.[Zi-Zhao], Ebrahimi, S.[Sayna], Sun, R.[Ruoxi], Zhang, H.[Han], Lee, C.Y.[Chen-Yu], Ren, X.Q.[Xiao-Qi], Su, G.L.[Guo-Long], Perot, V.[Vincent], Dy, J.[Jennifer], Pfister, T.[Tomas],
DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning,
ECCV22(XXVI:631-648).
Springer DOI 2211
BibRef

Hedegaard, L.[Lukas], Iosifidis, A.[Alexandros],
Continual 3D Convolutional Neural Networks for Real-time Processing of Videos,
ECCV22(IV:369-385).
Springer DOI 2211
BibRef

Jin, H.[Hyundong], Kim, E.[Eunwoo],
Helpful or Harmful: Inter-task Association in Continual Learning,
ECCV22(XI:519-535).
Springer DOI 2211
BibRef

Andle, J.[Joshua], Sekeh, S.Y.[Salimeh Yasaei],
Theoretical Understanding of the Information Flow on Continual Learning Performance,
ECCV22(XII:86-101).
Springer DOI 2211
BibRef

Tiwari, R.[Rishabh], Killamsetty, K.[Krishnateja], Iyer, R.[Rishabh], Shenoy, P.[Pradeep],
GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning,
CVPR22(99-108)
IEEE DOI 2210
Adaptation models, Data models, Pattern recognition, Task analysis, Optimization, Machine learning, Computer vision theory, Optimization methods BibRef

Yan, Q.S.[Qing-Sen], Gong, D.[Dong], Liu, Y.H.[Yu-Hang], van den Hengel, A.[Anton], Shi, J.Q.F.[Javen Qin-Feng],
Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning,
CVPR22(109-118)
IEEE DOI 2210
Correlation, Neurons, Interference, Machine learning, Reservoirs, Bayes methods, Machine learning, Deep learning architectures and techniques BibRef

Wang, Z.F.[Zi-Feng], Zhang, Z.Z.[Zi-Zhao], Lee, C.Y.[Chen-Yu], Zhang, H.[Han], Sun, R.[Ruoxi], Ren, X.Q.[Xiao-Qi], Su, G.[Guolong], Perot, V.[Vincent], Dy, J.[Jennifer], Pfister, T.[Tomas],
Learning to Prompt for Continual Learning,
CVPR22(139-149)
IEEE DOI 2210
Representation learning, Adaptation models, Codes, Predictive models, Data models, Pattern recognition, Representation learning BibRef

Xue, M.Q.[Meng-Qi], Zhang, H.[Haofei], Song, J.[Jie], Song, M.L.[Ming-Li],
Meta-attention for ViT-backed Continual Learning,
CVPR22(150-159)
IEEE DOI 2210
Learning systems, Degradation, Codes, Transformers, Pattern recognition, Convolutional neural networks, Deep learning architectures and techniques BibRef

Wang, Z.[Zhen], Liu, L.[Liu], Kong, Y.J.[Ya-Jing], Guo, J.X.[Jia-Xian], Tao, D.C.[Da-Cheng],
Online Continual Learning with Contrastive Vision Transformer,
ECCV22(XX:631-650).
Springer DOI 2211
BibRef

Wang, Z.[Zhen], Liu, L.[Liu], Duan, Y.Q.[Yi-Qun], Kong, Y.J.[Ya-Jing], Tao, D.C.[Da-Cheng],
Continual Learning with Lifelong Vision Transformer,
CVPR22(171-181)
IEEE DOI 2210
Training, Learning systems, Neural networks, Interference, Benchmark testing, Transformers, Machine learning, Others, Representation learning BibRef

Gu, Y.[Yanan], Yang, X.[Xu], Wei, K.[Kun], Deng, C.[Cheng],
Not Just Selection, but Exploration: Online Class-Incremental Continual Learning via Dual View Consistency,
CVPR22(7432-7441)
IEEE DOI 2210
Training, Representation learning, Semantics, Neural networks, Benchmark testing, Streaming media, Recognition: detection, Representation learning BibRef

Simon, C.[Christian], Faraki, M.[Masoud], Tsai, Y.H.[Yi-Hsuan], Yu, X.[Xiang], Schulter, S.[Samuel], Suh, Y.[Yumin], Harandi, M.[Mehrtash], Chandraker, M.[Manmohan],
On Generalizing Beyond Domains in Cross-Domain Continual Learning,
CVPR22(9255-9264)
IEEE DOI 2210
Knowledge engineering, Measurement, Deep learning, Computational modeling, Neural networks, Pattern recognition, Machine learning BibRef

Bang, J.[Jihwan], Koh, H.[Hyunseo], Park, S.[Seulki], Song, H.[Hwanjun], Ha, J.W.[Jung-Woo], Choi, J.H.[Jong-Hyun],
Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries,
CVPR22(9265-9274)
IEEE DOI 2210
Art, Codes, Memory management, Semisupervised learning, Pattern recognition, Noise measurement, Self- semi- meta- unsupervised learning BibRef

Douillard, A.[Arthur], Ramé, A.[Alexandre], Couairon, G.[Guillaume], Cord, M.[Matthieu],
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion,
CVPR22(9275-9285)
IEEE DOI 2210
Representation learning, Deep learning, Memory management, Network architecture, Transformers, Market research, Decoding, Representation learning BibRef

Fini, E.[Enrico], da Costa, V.G.T.[Victor G. Turrisi], Alameda-Pineda, X.[Xavier], Ricci, E.[Elisa], Alahari, K.[Karteek], Mairal, J.[Julien],
Self-Supervised Models are Continual Learners,
CVPR22(9611-9620)
IEEE DOI 2210
Training, Representation learning, Visualization, Surveillance, Self-supervised learning, Data models, Self- semi- meta- Representation learning BibRef

Chen, G.[Geng], Zhang, W.D.[Wen-Dong], Lu, H.[Han], Gao, S.[Siyu], Wang, Y.[Yunbo], Long, M.S.[Ming-Sheng], Yang, X.K.[Xiao-Kang],
Continual Predictive Learning from Videos,
CVPR22(10718-10727)
IEEE DOI 2210
Training, Adaptation models, Art, Predictive models, Benchmark testing, Prediction algorithms, Self- semi- meta- unsupervised learning BibRef

Wan, T.S.T.[Timmy S. T.], Chen, J.C.[Jun-Cheng], Wu, T.Y.[Tzer-Yi], Chen, C.S.[Chu-Song],
Continual Learning for Visual Search with Backward Consistent Feature Embedding,
CVPR22(16681-16690)
IEEE DOI 2210
Representation learning, Visualization, Computational modeling, Coherence, Benchmark testing, Data models, Representation learning, retrieval BibRef

Davari, M.R.[Mohammad-Reza], Asadi, N.[Nader], Mudur, S.[Sudhir], Aljundi, R.[Rahaf], Belilovsky, E.[Eugene],
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning,
CVPR22(16691-16700)
IEEE DOI 2210
Representation learning, Training, Measurement, Supervised learning, Neural networks, Prototypes, Representation learning BibRef

Taufique, A.M.N.[Abu Md Niamul], Jahan, C.S.[Chowdhury Sadman], Savakis, A.[Andreas],
Unsupervised Continual Learning for Gradually Varying Domains,
CLVision22(3739-3749)
IEEE DOI 2210
Learning systems, Bridges, Adaptation models, Codes, Memory management BibRef

Ermis, B.[Beyza], Zappella, G.[Giovanni], Wistuba, M.[Martin], Rawal, A.[Aditya], Archambeau, C.[Cédric],
Continual Learning with Transformers for Image Classification,
CLVision22(3773-3780)
IEEE DOI 2210
Training, Adaptation models, Computational modeling, Neural networks, Training data, Predictive models BibRef

Carta, A.[Antonio], Cossu, A.[Andrea], Lomonaco, V.[Vincenzo], Bacciu, D.[Davide],
Ex-Model: Continual Learning from a Stream of Trained Models,
CLVision22(3789-3798)
IEEE DOI 2210
Learning systems, Data privacy, Computational modeling, Data models, Pattern recognition BibRef

Pelosin, F.[Francesco], Jha, S.[Saurav], Torsello, A.[Andrea], Raducanu, B.[Bogdan], van de Weijer, J.[Joost],
Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization,
CLVision22(3819-3828)
IEEE DOI 2210
Learning systems, Weight measurement, Image recognition, Surgery, Benchmark testing, Transformers, Stability analysis BibRef

He, J.P.[Jiang-Peng], Zhu, F.Q.[Feng-Qing],
Out-Of-Distribution Detection In Unsupervised Continual Learning,
CLVision22(3849-3854)
IEEE DOI 2210
Protocols, Annotations, Detectors, Pattern recognition, Task analysis BibRef

Kim, G.[Gyuhak], Esmaeilpour, S.[Sepideh], Xiao, C.[Changnan], Liu, B.[Bing],
Continual Learning Based on OOD Detection and Task Masking,
CLVision22(3855-3865)
IEEE DOI 2210
Training, Machine learning algorithms, Codes, Supervised learning, Data models BibRef

Gomez-Villa, A.[Alex], Twardowski, B.[Bartlomiej], Yu, L.[Lu], Bagdanov, A.D.[Andrew D.], van de Weijer, J.[Joost],
Continually Learning Self-Supervised Representations with Projected Functional Regularization,
CLVision22(3866-3876)
IEEE DOI 2210
Conferences, Self-supervised learning, Image representation, Pattern recognition BibRef

Karim, N.[Nazmul], Khalid, U.[Umar], Esmaeili, A.[Ashkan], Rahnavard, N.[Nazanin],
CNLL: A Semi-supervised Approach For Continual Noisy Label Learning,
CLVision22(3877-3887)
IEEE DOI 2210
Training, Codes, Purification, Benchmark testing, Performance gain BibRef

Merlin, G.[Gabriele], Lomonaco, V.[Vincenzo], Cossu, A.[Andrea], Carta, A.[Antonio], Bacciu, D.[Davide],
Practical Recommendations for Replay-Based Continual Learning Methods,
CL4REAL22(548-559).
Springer DOI 2208
BibRef

Kim, S.[Sohee], Lee, S.K.[Seung-Kyu],
Continual Learning with Neuron Activation Importance,
CIAP22(I:310-321).
Springer DOI 2205
BibRef

Barletti, T.[Tommaso], Biondi, N.[Niccoló], Pernici, F.[Federico], Bruni, M.[Matteo], del Bimbo, A.[Alberto],
Contrastive Supervised Distillation for Continual Representation Learning,
CIAP22(I:597-609).
Springer DOI 2205
BibRef

Davalas, C.[Charalampos], Michail, D.[Dimitrios], Diou, C.[Christos], Varlamis, I.[Iraklis], Tserpes, K.[Konstantinos],
Computationally Efficient Rehearsal for Online Continual Learning,
CIAP22(III:39-49).
Springer DOI 2205
BibRef

Yan, Z.[Zike], Tian, Y.X.[Yu-Xin], Shi, X.S.[Xue-Song], Guo, P.[Ping], Wang, P.[Peng], Zha, H.B.[Hong-Bin],
Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observations,
ICCV21(15762-15772)
IEEE DOI 2203
Geometry, Robot kinematics, Neural networks, Streaming media, Network architecture, Real-time systems, Scene analysis and understanding BibRef

Kim, C.D.[Chris Dongjoo], Jeong, J.[Jinseo], Moon, S.[Sangwoo], Kim, G.[Gunhee],
Continual Learning on Noisy Data Streams via Self-Purified Replay,
ICCV21(517-527)
IEEE DOI 2203
Training, Heart, Buildings, Information filters, Noise measurement, Recognition and classification, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

de Lange, M.[Matthias], Tuytelaars, T.[Tinne],
Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams,
ICCV21(8230-8239)
IEEE DOI 2203
Training, Representation learning, Memory management, Prototypes, Benchmark testing, Linear programming, Synchronization, Representation learning BibRef

Verwimp, E.[Eli], de Lange, M.[Matthias], Tuytelaars, T.[Tinne],
Rehearsal revealed: The limits and merits of revisiting samples in continual learning,
ICCV21(9365-9374)
IEEE DOI 2203
Computational modeling, Machine learning, Benchmark testing, Task analysis, Transfer/Low-shot/Semi/Unsupervised Learning, Recognition and classification BibRef

Cha, H.[Hyuntak], Lee, J.[Jaeho], Shin, J.[Jinwoo],
Co2L: Contrastive Continual Learning,
ICCV21(9496-9505)
IEEE DOI 2203
Representation learning, Visualization, Codes, Computational modeling, Benchmark testing, Representation learning BibRef

Cai, Z.P.[Zhi-Peng], Sener, O.[Ozan], Koltun, V.[Vladlen],
Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data,
ICCV21(8261-8270)
IEEE DOI 2203
Training, Measurement, Visualization, Schedules, Supervised learning, Coherence, Benchmark testing, Vision + other modalities BibRef

Lee, E.[Eugene], Huang, C.H.[Cheng-Han], Lee, C.Y.[Chen-Yi],
Few-Shot and Continual Learning with Attentive Independent Mechanisms,
ICCV21(9435-9444)
IEEE DOI 2203
Training, Deep learning, Adaptation models, Codes, Art, Computational modeling, Visual reasoning and logical representation BibRef

Gopalakrishnan, S.[Saisubramaniam], Singh, P.R.[Pranshu Ranjan], Fayek, H.[Haytham], Ramasamy, S.[Savitha], Ambikapathi, A.M.[Arul-Murugan],
Knowledge Capture and Replay for Continual Learning,
WACV22(337-345)
IEEE DOI 2202
Training, Deep learning, Visualization, Data privacy, Noise reduction, Neural networks, Knowledge representation, Semi- and Un- supervised Learning Continual Learning BibRef

He, J.P.[Jiang-Peng], Zhu, F.Q.[Feng-Qing],
Online Continual Learning Via Candidates Voting,
WACV22(1292-1301)
IEEE DOI 2202
Training, Data privacy, Memory management, Benchmark testing, Task analysis, Image classification, Vision Systems and Applications BibRef

Pham, X.C.[Xuan Cuong], Liew, A.W.C.[Alan Wee-Chung], Wang, C.[Can],
A Novel Class-wise Forgetting Detector in Continual Learning,
DICTA21(01-08)
IEEE DOI 2201
Training, Learning systems, Deep learning, Adaptation models, Digital images, Detectors, Data models, Online learning, Deep learning BibRef

Singh, P.R.[Pranshu Ranjan], Gopalakrishnan, S.[Saisubramaniam], ZhongZheng, Q.[Qiao], Suganthan, P.N.[Ponnuthurai N.], Ramasamy, S.[Savitha], Ambikapathi, A.[ArulMurugan],
Task-Agnostic Continual Learning Using Base-Child Classifiers,
ICIP21(794-798)
IEEE DOI 2201
Image processing, Complexity theory, Classification algorithms, Task analysis, Standards, Continual Learning, Hybrid Networks BibRef

Shi, Y.J.[Yu-Jun], Yuan, L.[Li], Chen, Y.P.[Yun-Peng], Feng, J.S.[Jia-Shi],
Continual Learning via Bit-Level Information Preserving,
CVPR21(16669-16678)
IEEE DOI 2111
Quantization (signal), Costs, Neural networks, Memory management, Reinforcement learning, Distance measurement, Pattern recognition BibRef

Verma, V.K.[Vinay Kumar], Liang, K.J.[Kevin J], Mehta, N.[Nikhil], Rai, P.[Piyush], Carin, L.[Lawrence],
Efficient Feature Transformations for Discriminative and Generative Continual Learning,
CVPR21(13860-13870)
IEEE DOI 2111
Learning systems, Computational modeling, Scalability, Neural networks, Transforms, Predictive models BibRef

Tang, S.X.[Shi-Xiang], Chen, D.P.[Da-Peng], Zhu, J.[Jinguo], Yu, S.J.[Shi-Jie], Ouyang, W.L.[Wan-Li],
Layerwise Optimization by Gradient Decomposition for Continual Learning,
CVPR21(9629-9638)
IEEE DOI 2111
Knowledge engineering, Deep learning, Computational modeling, Benchmark testing, Pattern recognition, Task analysis BibRef

Bang, J.[Jihwan], Kim, H.[Heesu], Yoo, Y.J.[Young-Joon], Ha, J.W.[Jung-Woo], Choi, J.H.[Jong-Hyun],
Rainbow Memory: Continual Learning with a Memory of Diverse Samples,
CVPR21(8214-8223)
IEEE DOI 2111
Training, Uncertainty, Codes, Memory management, Learning (artificial intelligence), Sampling methods BibRef

Wang, L.Y.[Li-Yuan], Yang, K.[Kuo], Li, C.X.[Chong-Xuan], Hong, L.Q.[Lan-Qing], Li, Z.G.[Zhen-Guo], Zhu, J.[Jun],
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning,
CVPR21(5379-5388)
IEEE DOI 2111
Deep learning, Systematics, Semisupervised learning, Benchmark testing, Generators BibRef

Zhang, C.[Chi], Song, N.[Nan], Lin, G.S.[Guo-Sheng], Zheng, Y.[Yun], Pan, P.[Pan], Xu, Y.H.[Ying-Hui],
Few-Shot Incremental Learning with Continually Evolved Classifiers,
CVPR21(12450-12459)
IEEE DOI 2111
Adaptation models, Machine learning algorithms, Training data, Benchmark testing, Power capacitors, Pattern recognition BibRef

Douillard, A.[Arthur], Valle, E.[Eduardo], Ollion, C.[Charles], Robert, T.[Thomas], Cord, M.[Matthieu],
Insights from the Future for Continual Learning,
CLVision21(3477-3486)
IEEE DOI 2109
Training, Computational modeling, Training data, Pattern recognition, Task analysis BibRef

Hayes, T.L.[Tyler L.], Kanan, C.[Christopher],
Selective Replay Enhances Learning in Online Continual Analogical Reasoning,
CLVision21(3497-3507)
IEEE DOI 2109
Measurement, Protocols, Neural networks, Reinforcement learning, Streaming media, Cognition, Pattern recognition BibRef

Kuo, N.I.H.[Nicholas I-Hsien], Harandi, M.[Mehrtash], Fourrier, N.[Nicolas], Walder, C.[Christian], Ferraro, G.[Gabriela], Suominen, H.[Hanna],
Plastic and Stable Gated Classifiers for Continual Learning,
CLVision21(3548-3553)
IEEE DOI 2109
Training, Knowledge engineering, Neural networks, Logic gates, Feature extraction, Robustness BibRef

Mai, Z.[Zheda], Li, R.[Ruiwen], Kim, H.W.[Hyun-Woo], Sanner, S.[Scott],
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning,
CLVision21(3584-3594)
IEEE DOI 2109
Training, Performance gain, Pattern recognition BibRef

Lomonaco, V.[Vincenzo], Pellegrini, L.[Lorenzo], Cossu, A.[Andrea], Carta, A.[Antonio], Graffieti, G.[Gabriele], Hayes, T.L.[Tyler L.], de Lange, M.[Matthias], Masana, M.[Marc], Pomponi, J.[Jary], van de Ven, G.M.[Gido M.], Mundt, M.[Martin], She, Q.[Qi], Cooper, K.[Keiland], Forest, J.[Jeremy], Belouadah, E.[Eden], Calderara, S.[Simone], Parisi, G.I.[German I.], Cuzzolin, F.[Fabio], Tolias, A.S.[Andreas S.], Scardapane, S.[Simone], Antiga, L.[Luca], Ahmad, S.[Subutai], Popescu, A.[Adrian], Kanan, C.[Christopher], van de Weijer, J.[Joost], Tuytelaars, T.[Tinne], Bacciu, D.[Davide], Maltoni, D.[Davide],
Avalanche: an End-to-End Library for Continual Learning,
CLVision21(3595-3605)
IEEE DOI 2109
Training, Deep learning, Machine learning algorithms, Collaboration, Libraries BibRef

Mirzadeh, S.I.[Seyed Iman], Ghasemzadeh, H.[Hassan],
CL-Gym: Full-Featured PyTorch Library for Continual Learning,
OmniCV21(3616-3622)
IEEE DOI 2109
Philosophical considerations, Learning (artificial intelligence), Libraries BibRef

Buzzega, P.[Pietro], Boschini, M.[Matteo], Porrello, A.[Angelo], Calderara, S.[Simone],
Rethinking Experience Replay: a Bag of Tricks for Continual Learning,
ICPR21(2180-2187)
IEEE DOI 2105
Degradation, Neural networks, Proposals, Erbium, Standards BibRef

Li, X.O.[Xia-Obin], Shan, L.L.[Lian-Lei], Li, M.L.[Ming-Long], Wang, W.Q.[Wei-Qiang],
Energy Minimum Regularization in Continual Learning,
ICPR21(6404-6409)
IEEE DOI 2105
Learning systems, Sensitivity, Animals, Solids, Minimization, Pattern recognition, Task analysis BibRef

Ho, C.H.[Chih-Hsing], Tsai, S.H.L.[Shang-Ho Lawrence],
RSAC: Regularized Subspace Approximation Classifier for Lightweight Continuous Learning,
ICPR21(6680-6687)
IEEE DOI 2105
Training, Memory management, Training data, Approximation algorithms, Classification algorithms, Streaming Learning BibRef

Kim, C.D.[Chris Dongjoo], Jeong, J.[Jinseo], Kim, G.[Gunhee],
Imbalanced Continual Learning with Partitioning Reservoir Sampling,
ECCV20(XIII:411-428).
Springer DOI 2011
BibRef

Fini, E.[Enrico], Lathuilière, S.[Stéphane], Sangineto, E.[Enver], Nabi, M.[Moin], Ricci, E.[Elisa],
Online Continual Learning Under Extreme Memory Constraints,
ECCV20(XXVIII:720-735).
Springer DOI 2011
BibRef

Prabhu, A.[Ameya], Torr, P.H.S.[Philip H. S.], Dokania, P.K.[Puneet K.],
GDUMB: A Simple Approach that Questions Our Progress in Continual Learning,
ECCV20(II:524-540).
Springer DOI 2011
BibRef

Lomonaco, V., Maltoni, D., Pellegrini, L.,
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches,
CLVision20(989-998)
IEEE DOI 2008
Training, Robots, Videos, Object recognition, Benchmark testing, Computational modeling BibRef

Silver, D.L., Mahfuz, S.,
Generating Accurate Pseudo Examples for Continual Learning,
CLVision20(1035-1042)
IEEE DOI 2008
Task analysis, Training, Probability distribution, Knowledge engineering, Input variables, Neural networks BibRef

Parshotam, K., Kilickaya, M.,
Continual Learning of Object Instances,
CLVision20(907-914)
IEEE DOI 2008
Automobiles, Task analysis, Measurement, Training, Data models, Visualization, Companies BibRef

Mirzadeh, S.I., Farajtabar, M., Ghasemzadeh, H.,
Dropout as an Implicit Gating Mechanism For Continual Learning,
CLVision20(945-951)
IEEE DOI 2008
Task analysis, Neurons, Stability analysis, Training, Standards, Logic gates, Knowledge engineering BibRef

Zhang, J.[Jie], Zhang, J.T.[Jun-Ting], Ghosh, S.[Shalini], Li, D.W.[Da-Wei], Zhu, J.W.[Jing-Wen], Zhang, H.M.[He-Ming], Wang, Y.L.[Ya-Lin],
Regularize, Expand and Compress: NonExpansive Continual Learning,
WACV20(843-851)
IEEE DOI 2006
Task analysis, Computational modeling, Network architecture, Neural networks, Knowledge engineering, Correlation BibRef

Ostapenko, O.[Oleksiy], Puscas, M.[Mihai], Klein, T.[Tassilo], Jahnichen, P.[Patrick], Nabi, M.[Moin],
Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning,
CVPR19(11313-11321).
IEEE DOI 2002
BibRef

Murata, K.[Kengo], Toyota, T.[Tetsuya], Ohara, K.[Kouzou],
What is Happening Inside a Continual Learning Model?: A Representation-Based Evaluation of Representational Forgetting,
CLVision20(952-956)
IEEE DOI 2008
Task analysis, Erbium, Measurement, Learning systems, Standards, Neural networks, Data models BibRef

Abati, D., Tomczak, J., Blankevoort, T., Calderara, S., Cucchiara, R., Bejnordi, B.E.,
Conditional Channel Gated Networks for Task-Aware Continual Learning,
CVPR20(3930-3939)
IEEE DOI 2008
Task analysis, Logic gates, Training, Computational modeling, Neural networks, Machine learning, Computer architecture BibRef

Lee, J., Hong, H.G., Joo, D., Kim, J.,
Continual Learning With Extended Kronecker-Factored Approximate Curvature,
CVPR20(8998-9007)
IEEE DOI 2008
Task analysis, Neural networks, Mathematical model, Learning systems, Optimization, Network architecture, Training BibRef

Kim, J., Kim, J., Kwak, N.,
StackNet: Stacking feature maps for Continual learning,
CLVision20(975-982)
IEEE DOI 2008
Task analysis, Indexes, Training, Data models, Biological neural networks, Stacking, Machine learning BibRef

Du, X., Li, Z., Seo, J., Liu, F., Cao, Y.,
Noise-based Selection of Robust Inherited Model for Accurate Continual Learning,
CLVision20(983-988)
IEEE DOI 2008
Pattern recognition BibRef

Aljundi, R.[Rahaf], Kelchtermans, K.[Klaas], Tuytelaars, T.[Tinne],
Task-Free Continual Learning,
CVPR19(11246-11255).
IEEE DOI 2002
BibRef

Park, D.M.[Dong-Min], Hong, S.[Seokil], Han, B.H.[Bo-Hyung], Lee, K.M.[Kyoung Mu],
Continual Learning by Asymmetric Loss Approximation With Single-Side Overestimation,
ICCV19(3334-3343)
IEEE DOI 2004
function approximation, learning (artificial intelligence), neural nets, asymmetric loss approximation, Scalability BibRef

El Khatib, A.[Alaa], Karray, F.[Fakhri],
Strategies for Improving Single-Head Continual Learning Performance,
ICIAR19(I:452-460).
Springer DOI 1909
Forgetting. Problem is also not all data is available at once. BibRef

Hayes, T.L., Kemker, R., Cahill, N.D., Kanan, C.,
New Metrics and Experimental Paradigms for Continual Learning,
DeepLearnRV18(2112-21123)
IEEE DOI 1812
Robots, Measurement, Training, Task analysis, Computational modeling, Neural networks, Data models BibRef

Zhai, M.Y.[Meng-Yao], Chen, L.[Lei], Mori, G.[Greg],
Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation,
CVPR21(2246-2255)
IEEE DOI 2111
Deep learning, Costs, Heuristic algorithms, Memory management, Filtering algorithms, Information filters, Generators BibRef

Zhai, M.Y.[Meng-Yao], Chen, L.[Lei], He, J.W.[Jia-Wei], Nawhal, M.[Megha], Tung, F.[Frederick], Mori, G.[Greg],
Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation,
ECCV20(XXI:397-413).
Springer DOI 2011
BibRef
Earlier: A1, A2, A5, A3, A4, A6:
Lifelong GAN: Continual Learning for Conditional Image Generation,
ICCV19(2759-2768)
IEEE DOI 2004
image processing, learning (artificial intelligence), neural nets, continual learning, deep neural networks, Training data BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Active Learning .


Last update:Jun 17, 2024 at 21:38:11