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.[Ale],
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
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,
VCL23(3504-3509)
IEEE DOI
2401
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
B, P.[Prasanna],
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.[Junjiao],
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.[Anaďs],
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
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],
Lathuiličre, 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 .