Incremental Learning Repository: A collection of documents, papers, source code, and talks for incremental learning.
Keywords: Incremental Learning, Continual Learning, Continuous Learning, Lifelong Learning, Catastrophic Forgetting
CATALOGUE
Quick Start ✨ Survey ✨ Papers by Categories ✨ Datasets ✨ Tutorial, Workshop, & Talks
Continual Learning | Papers With Code
Incremental Learning | Papers With Code
Class Incremental Learning from the Past to Present by 思悥 | 知乎 (In Chinese)
A Little Survey of Incremental Learning | 知乎 (In Chinese)
Origin of the Study
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Catastrophic Forgetting, Rehearsal and Pseudorehearsal(1995)[paper]
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Catastrophic forgetting in connectionist networks(1999)[paper]
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Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem(1989)[paper]
Toolbox & Framework
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[CLHive] [code]
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[PTIL] Prompt-based Incremental Learning Toolbox [code]
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[LAMDA-PILOT] PILOT: A Pre-Trained Model-Based Continual Learning Toolbox(arXiv 2023)[paper][code]
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[FACIL] Class-incremental learning: survey and performance evaluation on image classification(TPAMI 2022)[paper][code]
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[Avalanche] Avalanche: An End-to-End Library for Continual Learning(CVPR 2021)[paper][code]
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[PyCIL] PyCIL: A Python Toolbox for Class-Incremental Learning(arXiv 2021)[paper][code]
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[Mammoth] An Extendible (General) Continual Learning Framework for Pytorch [code]
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[PyContinual] An Easy and Extendible Framework for Continual Learning[code]
Books
- Lifelong Machine Learning [Link]
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A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning(arXiv 2023)[github]
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Deep Class-Incremental Learning: A Survey(arXiv 2023)[paper][code]
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A Comprehensive Survey of Continual Learning: Theory, Method and Application(arxiv 2023)[paper]
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[FACIL] Class-incremental learning: survey and performance evaluation on image classification(TPAMI 2022)[paper][code]
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Online Continual Learning in Image Classification: An Empirical Survey (Neurocomputing 2021)[paper]
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A continual learning survey: Defying forgetting in classification tasks (TPAMI 2021) [paper]
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Rehearsal revealed: The limits and merits of revisiting samples in continual learning (ICCV 2021)[paper]
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Continual Lifelong Learning in Natural Language Processing: A Survey (COLING 2020) [paper]
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A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks (Neural Networks 2020) [paper]
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Embracing Change: Continual Learning in Deep Neural Networks(Trends in Cognitive Sciences 2020)[paper]
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Towards Continual Reinforcement Learning: A Review and Perspectives(arXiv 2020)[paper]
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Class-incremental learning: survey and performance evaluation(arXiv 2020) [paper]
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A comprehensive, application-oriented study of catastrophic forgetting in DNNs (ICLR 2019) [paper]
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Three scenarios for continual learning (arXiv 2019) [paper]
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Continual lifelong learning with neural networks: A review(arXiv 2019)[paper]
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类别增量学习研究进展和性能评价 (自动化学报 2023)[paper]
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How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?(NeurIPS 2022)[paper]
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[WPTP] A Theoretical Study on Solving Continual Learning(NeurIPS 2022)[paper][code]
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The Challenges of Continuous Self-Supervised Learning(ECCV 2022)[peper]
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Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions(NeurIPS 2022)[paper]
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A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal(NeurIPS 2022)[paper][code]
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Exploring Example Influence in Continual Learning(NeurIPS 2022)[paper]
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Biological underpinnings for lifelong learning machines(Nat. Mach. Intell. 2022)[paper]
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Probing Representation Forgetting in Supervised and Unsupervised Continual Learning(CVPR 2022)[paper][code]
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[OpenLORIS-Object] Towards Lifelong Object Recognition: A Dataset and Benchmark(Pattern Recognit 2022)[paper]
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Probing Representation Forgetting in Supervised and Unsupervised Continual Learning (CVPR 2022) [paper]
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Learngene: From Open-World to Your Learning Task (AAAI 2022) [paper]
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Continual Normalization: Rethinking Batch Normalization for Online Continual Learning (ICLR 2022) [paper]
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[CLEVA-Compass] CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability (ICLR 2022) [paper][code]
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Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting (ICLR 2022) [paper]
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[CKL] Towards Continual Knowledge Learning of Language Models (ICLR 2022) [paper]
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Pretrained Language Model in Continual Learning: A Comparative Study (ICLR 2022) [paper]
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Effect of scale on catastrophic forgetting in neural networks (ICLR 2022) [paper]
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LifeLonger: A Benchmark for Continual Disease Classification(arXiv 2022)[paper]
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[CDDB] A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials(arXiv 2022)[paper]
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[BN Tricks] Diagnosing Batch Normalization in Class Incremental Learning(arXiv 2022)[paper]
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Architecture Matters in Continual Learning(arXiv 2022)[paper]
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Learning where to learn: Gradient sparsity in meta and continual learning(NeurIPS 2021) [paper]
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Continuous Coordination As a Realistic Scenario for Lifelong Learning(ICML 2021)[paper]
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Understanding the Role of Training Regimes in Continual Learning (NeurIPS 2020)[paper]
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Optimal Continual Learning has Perfect Memory and is NP-HARD (ICML 2020)[paper]
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[FSCIL] Few-shot Class Incremental Learning [Link]
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[DCIL] Decentralized Class Incremental Learning [paper][Setting]
Tips: you can use ctrl+F to match abbreviations with articles, or browse the paper list below.
| Network Structure | Rehearsal | |
|---|---|---|
| 2024 | SEED(ICLR 2024)[paper] CAMA(ICLR 2024)[paper][code] SFR(ICLR 2024)[paper][code] HLOP(ICLR 2024)[paper] TPL(ICLR 2024)[paper][code] EFC(ICLR 2024)[paper] PICLE(ICLR 2024)[paper] OVOR(ICLR 2024)[paper][code] PEC(ICLR 2024)[paper][code] refresh learning(ICLR 2024)[paper] POCON(WACV 2024)[paper] CLTA(WACV 2024)[paper][code] FG-KSR(AAAI 2024)[paper][code] |
MOSE(CVPR 2024)[paper][code] AISEOCL(Pattern Recognition 2024)[paper] AF-FCL(ICLR 2024)[paper][code] DietCL(ICLR 2024)[paper] BGS(ICLR 2024)[paper] DMU(WACV 2024)[paper][code] |
| 2023 | A-Prompts (arXiv 2023)[paper] ESN(AAAI 2023)[paper][code]  RevisitingCIL(arXiv 2023)[paper][code]  LwP(ICLR 2023)[paper] SDMLP(ICLR 2023)[paper] SaLinA(ICLR 2023)[paper][code] BEEF(ICLR 2023)[paper][code]  WaRP(ICLR 2023)[paper] OBC(ICLR 2023)[paper] NC-FSCIL(ICLR 2023)[paper][code]  iVoro(ICLR 2023)[paper] DAS(ICLR 2023)[paper] Progressive Prompts(ICLR 2023)[paper] SDP(ICLR 2023)[paper][code]  iLDR(ICLR 2023)[paper] SoftNet-FSCIL(ICLR 2023)[paper][code]  PAR(CVPR 2023)[paper] PETAL(CVPR 2023)[paper][code]  SAVC(CVPR 2023)[paper][code]  CODA-Prompt(CVPR 2023)[paper][code]  |
FeTrIL(WACV 2023)[paper][code] ESMER(ICLR 2023)[paper][code]  MEMO(ICLR 2023)[paper][code]  CUDOS(ICLR 2023)[paper] ACGAN(ICLR 2023)[paper][code]  TAMiL(ICLR 2023)[paper][code]  RSOI(CVPR 2023)[paper][code]  TBBN(CVPR 2023)[paper] AMSS(CVPR 2023)[paper] DGCL(CVPR 2023)[paper] PCR(CVPR 2023)[paper][code]  FMWISS(CVPR 2023)[paper] CL-DETR(CVPR 2023)[paper][code]  PIVOT(CVPR 2023)[paper] CIM-CIL(CVPR 2023)[paper][code]  DNE(CVPR 2023)[paper] |
| 2022 | RD-IOD(ACM Trans 2022)[paper] NCM(arXiv 2022)[paper] IPP(arXiv 2022)[paper] Incremental-DETR(arXiv 2022)[paper] ELI(CVPR 2022)[paper] CASSLE(CVPR 2022)[paper][code]  iFS-RCNN(CVPR 2022)[paper] WILSON(CVPR 2022)[paper][code]  Connector(CVPR 2022)[paper][code]  PAD(CVPR 2022)[paper] ERD(CVPR 2022)[paper][code]  AFC(CVPR 2022)[paper][code]  FACT(CVPR 2022)[paper][code]  L2P(CVPR 2022)[paper][code]  MEAT(CVPR 2022)[paper][code]  RCIL(CVPR 2022)[paper][code]  ZITS(CVPR 2022)[paper][code]  MTPSL(CVPR 2022)[paper][code]  MMA(CVPR-Workshop 2022)[paper] CoSCL(ECCV 2022)[paper][code]  AdNS(ECCV 2022)[paper] ProCA(ECCV 2022)[paper][code]  R-DFCIL(ECCV 2022)[paper][code]  S3C(ECCV 2022)[paper][code]  H^2^(ECCV 2022)[paper] DualPrompt(ECCV 2022)[paper] ALICE(ECCV 2022)[paper][code]  RU-TIL(ECCV 2022)[paper][code]  FOSTER(ECCV 2022)[paper] SSR(ICLR 2022)[paper][code]  RGO(ICLR 2022)[paper] TRGP(ICLR 2022)[paper] AGCN(ICME 2022)[paper][code]  WSN(ICML 2022)[paper][code]  NISPA(ICML 2022)[paper][code]  S-FSVI(ICML 2022)[paper][code]  CUBER(NeurIPS 2022)[paper] ADA(NeurIPS 2022)[paper] CLOM(NeurIPS 2022)[paper] S-Prompt(NeurIPS 2022)[paper] ALIFE(NIPS 2022)[paper] PMT(NIPS 2022)[paper] STCISS(TNNLS 2022)[paper] DSN(TPAMI 2022)[paper] MgSvF(TPAMI 2022)[paper] TransIL(WACV 2022)[paper] |
NER-FSCIL(ACL 2022)[paper] LIMIT(arXiv 2022)[paper] EMP(arXiv 2022)[paper] SPTM(CVPR 2022)[paper] BER(CVPR 2022)[paper] Sylph(CVPR 2022)[paper] MetaFSCIL(CVPR 2022)[paper] FCIL(CVPR 2022)[paper][code]  FILIT(CVPR 2022)[paper] PuriDivER(CVPR 2022)[paper][code]  SNCL(CVPR 2022)[paper] DVC(CVPR 2022)[paper][code]  CVS(CVPR 2022)[paper] CPL(CVPR 2022)[paper] GCR(CVPR 2022)[paper] LVT(CVPR 2022)[paper] vCLIMB(CVPR 2022)[paper][code] Learn-to-Imagine(CVPR 2022)[paper][code]  DCR(CVPR 2022)[paper] DIY-FSCIL(CVPR 2022)[paper] C-FSCIL(CVPR 2022)[paper][code]  SSRE(CVPR 2022)[paper] CwD(CVPR 2022)[paper][code]  MSL(CVPR 2022)[paper] DyTox(CVPR 2022)[paper][code]  X-DER(ECCV 2022)[paper] clsss-iNCD(ECCV 2022)[paper][code]  ARI(ECCV 2022)[paper][code]  Long-Tailed-CIL(ECCV 2022)[paper][code]  LIRF(ECCV 2022)[paper] DSDM(ECCV 2022)[paper][code]  CVT(ECCV 2022)[paper] TwF(ECCV 2022)[paper][code]  CSCCT(ECCV 2022)[paper][code]  DLCFT(ECCV 2022)[paper] ERDR(ECCV2022)[paper] NCDwF(ECCV2022)[paper] CoMPS(ICLR 2022)[paper] i-fuzzy(ICLR 2022)[paper][code]  CLS-ER(ICLR 2022)[paper][code]  MRDC(ICLR 2022)[paper][code]  OCS(ICLR 2022)[paper] InfoRS(ICLR 2022)[paper] ER-AML(ICLR 2022)[paper][code]  FAS(ICLR 2022)[paper] LUMP(ICLR 2022)[paper] CF-IL(ICLR 2022)[paper][code]  LFPT5(ICLR 2022)[paper][code]  Model Zoo(ICLR 2022)[paper] OCM(ICML 2022)[paper][code]  DRO(ICML 2022)[paper][code]  EAK(ICPR 2022)[paper] RAR(NeurIPS 2022)[paper] LiDER(NeurIPS 2022)[paper] SparCL(NeurIPS 2022)[paper] ClonEx-SAC(NeurIPS 2022)[paper] ODDL(NeurIPS 2022)[paper] CSSL(PRL 2022)[paper] MBP(TNNLS 2022)[paper] CandVot(WACV 2022)[paper] FlashCards(WACV 2022)[paper] |
| 2021 | Meta-DR(CVPR 2021)[paper] continual cross-modal retrieval(CVPR 2021)[paper] DER(CVPR 2021)[paper][code]  EFT(CVPR 2021)[paper][code]  PASS(CVPR 2021)[paper][code]  GeoDL(CVPR 2021)[paper][code]  IL-ReduNet(CVPR 2021)[paper] PIGWM(CVPR 2021)[paper] BLIP(CVPR 2021)[paper][code]  Adam-NSCL(CVPR 2021)[paper][code]  PLOP(CVPR 2021)[paper][code]  SDR(CVPR 2021)[paper][code]  SKD(CVPR 2021)[paper] Always Be Dreaming(ICCV 2021)[paper][code]  SPB(ICCV 2021)[paper] Else-Net(ICCV 2021)[paper] LCwoF-Framework(ICCV 2021)[paper] AFEC(NeurIPS 2021)[paper][code]  F2M(NeurIPS 2021)[paper][code]  NCL(NeurIPS 2021)[paper][code]  BCL(NeurIPS 2021)[paper][code]  Posterior Meta-Replay(NeurIPS 2021)[paper] MARK(NeurIPS 2021)[paper][code]  Co-occur(NeurIPS 2021)[paper][code]  LINC(AAAI 2021)[paper] CLNER(AAAI 2021)[paper] CLIS(AAAI 2021)[paper] PCL(AAAI 2021)[paper] MAS3(AAAI 2021)[paper] FSLL(AAAI 2021)[paper] VAR-GPs(ICML 2021)[paper] BSA(ICML 2021)[paper] GPM(ICLR 2021)[paper][code]  |
TMN(TNNLS 2021)[paper] RKD(AAAI 2021)[paper] AANets(CVPR 2021)[paper][code]  ORDisCo(CVPR 2021)[paper] DDE(CVPR 2021)[paper][code]  IIRC(CVPR 2021)[paper] Hyper-LifelongGAN(CVPR 2021)[paper] CEC(CVPR 2021)[paper] iMTFA(CVPR 2021)[paper] RM(CVPR 2021)[paper] LOGD(CVPR 2021)[paper] SPPR(CVPR 2021)[paper] LReID(CVPR 2021)[paper][code]  SS-IL(ICCV 2021)[paper] TCD(ICCV 2021)[paper] CLOC(ICCV 2021)[paper][code]  CoPE(ICCV 2021)[paper][code]  Co2L(ICCV 2021)[paper][code]  SPR(ICCV 2021)[paper] NACL(ICCV 2021)[paper] CL-HSCNet(ICCV 2021)[paper][code]  RECALL(ICCV 2021)[paper][code]  VAE(ICCV 2021)[paper] ERT(ICPR 2021)[paper][code]  KCL(ICML 2021)[paper][code]  MLIOD(TPAMI 2021)[paper][code]  BNS(NeurIPS 2021)[paper] FS-DGPM(NeurIPS 2021)[paper] SSUL(NeurIPS 2021)[paper] DualNet(NeurIPS 2021)[paper] classAug(NeurIPS 2021)[paper] GMED(NeurIPS 2021)[paper] BooVAE(NeurIPS 2021)[paper][code]  GeMCL(NeurIPS 2021)[paper] RMM(NIPS 2021)[paper][code]  LSF(IJCAI 2021)[paper] ASER(AAAI 2021)[paper][code]  CML(AAAI 2021)[paper][code]  HAL(AAAI 2021)[paper] MDMT(AAAI 2021)[paper] AU(WACV 2021)[paper] IDBR(NAACL 2021)[paper][code]  COIL(ACM MM 2021)[paper] |
| 2020 | CWR*(CVPR 2020)[paper] MiB(CVPR 2020)[paper][code]  K-FAC(CVPR 2020)[paper] SDC(CVPR 2020)[paper][code]  NLTF(AAAI 2020) [paper] CLCL(ICLR 2020)[paper][code]  APD(ICLR 2020)[paper] HYPERCL(ICLR 2020)[paper][code]  CN-DPM(ICLR 2020)[paper] UCB(ICLR 2020)[paper][code]  CLAW(ICLR 2020)[paper] CAT(NeurIPS 2020)[paper][code]  AGS-CL(NeurIPS 2020)[paper] MERLIN(NeurIPS 2020)[paper][code]  OSAKA(NeurIPS 2020)[paper][code]  RATT(NeurIPS 2020)[paper] CCLL(NeurIPS 2020)[paper] CIDA(ECCV 2020)[paper] GraphSAIL(CIKM 2020)[paper] ANML(ECAI 2020)[paper][code]  ICWR(BMVC 2020)[paper] DAM(TPAMI 2020)[paper] OGD(PMLR 2020)[paper] MC-OCL(ECCV2020)[paper][code]  RCM(ECCV 2020)[paper][code]  OvA-INN(IJCNN 2020)[paper] XtarNet(ICLM 2020)[paper][code]  DMC(WACV 2020)[paper] |
iTAML(CVPR 2020)[paper][code] FSCIL(CVPR 2020)[paper][code]  GFR(CVPR 2020)[paper][code]  OSIL(CVPR 2020)[paper] ONCE(CVPR 2020)[paper] WA(CVPR 2020)[paper][code] CGATE(CVPR 2020)[paper][code]  Mnemonics Training(CVPR 2020)[paper][code] MEGA(NeurIPS 2020)[paper] GAN Memory(NeurIPS 2020)[paper][code]  Coreset(NeurIPS 2020)[paper] FROMP(NeurIPS 2020)[paper][code]  DER(NeurIPS 2020)[paper][code]  InstAParam(NeurIPS 2020)[paper] BOCL(AAAI 2020)[paper] REMIND(ECCV 2020)[paper][code]  ACL(ECCV 2020)[paper][code]  TPCIL(ECCV 2020)[paper] GDumb(ECCV 2020)[paper][code]  PRS(ECCV 2020)[paper] PODNet(ECCV 2020)[paper][code]  FA(ECCV 2020)[paper] L-VAEGAN(ECCV 2020)[paper] Piggyback GAN(ECCV 2020)[paper][code]  IDA(ECCV 2020)[paper] RCM(ECCV 2020)[paper] LAMOL(ICLR 2020)[paper][code]  FRCL(ICLR 2020)[paper][code]  GRS(ICLR 2020)[paper] Brain-inspired replay(Natrue Communications 2020)[paper][code]  CLIFER(FG 2020)[paper] ScaIL(WACV 2020)[paper][code]  ARPER(EMNLP 2020)[paper] DnR(COLING 2020)[paper] ADER(RecSys 2020)[paper][code]  MUC(ECCV 2020)[paper][code]  |
| 2019 | LwM(CVPR 2019)[paper] CPG(NeurIPS 2019)[paper][code]  UCL(NeurIPS 2019)[paper] OML(NeurIPS 2019)[paper][code]  ALASSO(ICCV 2019)[paper] Learn-to-Grow(PMLR 2019)[paper] OWM(Nature Machine Intelligence 2019)[paper][code]  |
LUCIR(CVPR 2019)[paper][code] TFCL(CVPR 2019)[paper] GD(CVPR 2019)[paper][code]  DGM(CVPR 2019)[paper] BiC(CVPR 2019)[paper][code]  MER(ICLR 2019)[paper][code] PGMA(ICLR 2019)[paper] A-GEM(ICLR 2019)[paper][code]  IL2M(ICCV 2019)[paper] ILCAN(ICCV 2019)[paper] Lifelong GAN(ICCV 2019)[paper] GSS(NIPS 2019)[paper] ER(NIPS 2019)[paper] MIR(NIPS 2019)[paper][code]  RPS-Net(NIPS 2019)[paper] CLEER(IJCAI 2019)[paper] PAE(ICMR 2019)[paper][code]  |
| 2018 | PackNet(CVPR 2018)[paper][code] OLA(NIPS 2018)[paper] RCL(NIPS 2018)[paper][code]  MARL(ICLR 2018)[paper] DEN(ICLR 2018)[paper][code]  P&C(ICML 2018)[paper] Piggyback(ECCV 2018)[paper][code] RWalk(ECCV 2018)[paper] MAS(ECCV 2018)[paper][code]  R-EWC(ICPR 2018)[paper][code]  HAT(PMLR 2018)[paper][code]  |
MeRGANs(NIPS 2018)[paper][code] EEIL(ECCV 2018)[paper][code]  Adaptation by Distillation(ECCV 2018)[paper] ESGR(BMVC 2018)[paper][code]  VCL(ICLR 2018)[paper] FearNet(ICLR 2018)[paper] DGDMN(ICLR 2018)[paper] |
| 2017 | Expert Gate(CVPR 2017)[paper][code] ILOD(ICCV 2017)[paper][code]  EBLL(ICCV2017)[paper] IMM(NIPS 2017)[paper][code]  SI(ICML 2017)[paper][code]  EWC(PNAS 2017)[paper][code]  |
iCARL(CVPR 2017)[paper][code] GEM(NIPS 2017)[paper][code]  DGR(NIPS 2017)[paper][code]  |
| 2016 | LwF(ECCV 2016)[paper][code] |
Data decentralized incremental learning
- [DCID] Deep Class Incremental Learning from Decentralized Data(TNNLS 2022)[paper][code]
- [GLFC] Federated Class-Incremental Learning(CVPR 2022)[paper][code]
- [FedWeIT] Federated Continual Learning with Weighted Inter-client Transfer(ICML 2021)[paper][code]
Data centralized incremental learning
All other studies aforementioned except those already in the 'Decentralized' section.
| datasets | describes |
|---|---|
| ImageNet | There are 1.28 million training images and 50,000 validation images in over 1,000 categories. Usually crop into 224×224 color image |
| TinyImageNet | Contains 100,000 64×64 color images of 200 categories (500 per category). Each class has 500 training images, 50 validation images, and 50 test images. |
| MiniImageNet | This dataset is a subset of ImageNet used for few-shot learning. It consists of 60, 000 colour images of size 84 × 84 with 100 classes, each having 600 examples. |
| SubImageNet | This dataset is a 100-class subset of ImageNet's random sample, which contains approximately 130,000 images for training and 5,000 images for testing. |
| CIFAR-10/100 | Both datasets contain 60,000 natural RGB images of the size 32 × 32, including 50,000 training and 10,000 test images. CIFAR10 has 10 classes, while CIFAR100 has 100 classes. |
| CORe50 | This dataset consists of 164,866 128×128 RGB-D images: 11 sessions × 50 objects × (around 300) frames per session. Github CORe50: a New Dataset and Benchmark for Continuous Object Recognition |
| OpenLORIS-Object | This is the first real-world dataset for robotic vision with independent and quantifiable environmental factors, compared with other lifelong learning datasets, with 186 instances, 63 categories and 2,138,050 images. |
Life-Long learning | 李宏毅
Life-long Learning: [ppt] [pdf]
Catastrophic Forgetting [Chinese] [English]
Mitigating Catastrophic Forgetting [Chinese] [English]
Meta Learning : Learn to Learn [Chinese]
Continual AI Lecture
Open World Lifelong Learning | A Continual Machine Learning Course
Prompting-based Continual Learning | Continual AI
VALSE Webinar (In Chinese)
20211215【学无止境：深度连续学习】洪晓鹏：记忆拓扑保持的深度增量学习方法
20211215【学无止境：深度连续学习】李玺：基于深度神经网络的持续性学习理论与方法
ACM MULTIMEDIA
ACM2021 Few-shot Learning for Multi-Modality Tasks
CVPR Workshop
CVPR 2022 Workshop on Continual Learning in Computer Vision
CVPR2021 Workshop on Continual Learning in Computer Vision
CVPR2020 Workshop on Continual Learning in Computer Vision
CVPR2017 Continuous and Open-Set Learning Workshop
ICML Tutorial/Workshop
ICML 2021 Workshop on Theory and Foundation of Continual Learning
ICML 2021 Tutorial on Continual Learning with Deep Architectures
ICML2020 Workshop on Continual Learning
NeurIPS Workshop
NeurIPS2021 4th Robot Learning Workshop: Self-Supervised and Lifelong Learning
NeurIPS2018 Continual learning Workshop
NeurIPS2016 Continual Learning and Deep Networks Workshop
IJCAI Workshop
IJCAI 2021 International Workshop on Continual Semi-Supervised Learning
ContinualAI wiki
A Non-profit Research Organization and Open Community on Continual Learning for AI
CoLLAs
Conference on Lifelong Learning Agents - CoLLAs 2022
achieved
3rd CLVISION CVPR Workshop Challenge 2022
IJCAI 2021 - International Workshop on Continual Semi-Supervised Learning
2rd CLVISION CVPR Workshop Challenge 2021
1rd CLVISION CVPR Workshop Challenge 2020
[1] https://github.com/xialeiliu/Awesome-Incremental-Learning
Should there be any concerns on this page, please don't hesitate to let us know via hongxiaopeng@ieee.org or xl330@126.com.
- Continual Instruction Tuning for Large Multimodal Models [paper]
- Continual Adversarial Defense [paper][code]
- Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay [paper][code]
- Class Incremental Learning for Adversarial Robustnes [paper]
- KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All [paper]
- Prompt Gradient Projection for Continual Learning [paper]
- [MOSE] Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation(CVPR 2024) [paper][code]
- [AISEOCL] Adaptive instance similarity embedding for online continual learning (Pattern Recognition 2024) [paper]
- [SEED] Divide and not forget: Ensemble of selectively trained experts in Continual Learning(ICLR 2024) [paper]
- [CAMA] Online Continual Learning for Interactive Instruction Following Agents(ICLR 2024) [paper][code]
- [SFR]] Function-space Parameterization of Neural Networks for Sequential Learning(ICLR2024) [paper][code]
- [HLOP] Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks(ICLR 2024) [paper]
- [TPL] Class Incremental Learning via Likelihood Ratio Based Task Prediction(ICLR 2024) [paper][code]
- [AF-FCL] Accurate Forgetting for Heterogeneous Federated Continual Learning(ICLR 2024) [paper][code]
- [EFC] Elastic Feature Consolidation For Cold Start Exemplar-Free Incremental Learning(ICLR 2024) [paper]
- [DietCL] Continual Learning on a Diet:Learning from Sparsely Labeled Streams Under Constrained Computation(ICLR 2024) [paper]
- [PICLE] A Probabilistic Framework for Modular Continual Learning(ICLR 2024) [paper]
- OVOR OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning(ICLR 2024) [paper][code]
- [BGS] Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline(ICLR 2024) [paper]
- [PEC] Prediction Error-based Classification for Class-Incremental Learning(ICLR 2024) [paper][code]
- [refresh learning] A Unified and General Framework for Continual Learning(ICLR 2024) [paper]
- [CPPO] CPPO: Continual Learning for Reinforcement Learning with Human Feedback(ICLR 2024) [paper]
- [JARe] Scalable Language Model with Generalized Continual Learning(ICLR 2024) [paper]
- [POCON] Plasticity-Optimized Complementary Networks for Unsupervised Continual(WACV 2024) [paper]
- [DMU] Online Class-Incremental Learning For Real-World Food Image Classification(WACV 2024) [paper][code]
- [CLTA] Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning(WACV 2024) [paper][code]
- [FG-KSR] Fine-Grained Knowledge Selection and Restoration for Non-Exemplar Class Incremental Learning(AAAI 2024) [paper][code]
- [PRD] Prototype-Sample Relation Distillation: Towards Replay-FreeContinual Learning(ICML 2023) [paper]
- A Unified Continual Learning Framework with General Parameter-Efficient Tuning(ICCV 2023) [paper][code]
- Cross-Modal Alternating Learning with Task-Aware Representations for Continual Learning(TMM 2023) [paper][code]
- Semantic Knowledge Guided Class-Incremental Learning(TCSVT 2023) [paper]
- Non-Exemplar Class-Incremental Learning via Adaptive Old Class Reconstruction(ACM MM 2023) [paper][code]
- [HiDe-Prompt] Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality(NeurIPS 2023)[paper][code]
- TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion(NeurIPS 2023)[paper]
- [AdaB2N] Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation(NeurIPS 2023)[paper][[code]]](https://github.com/lvyilin/AdaB2N)
- Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning(ICCV 2023)[paper]
- Decouple Before Interact: Multi-Modal Prompt Learning for Continual Visual Question Answering(ICCV 2023)[paper]
- Prototype Reminiscence and Augmented Asymmetric Knowledge Aggregation for Non-Exemplar Class-Incremental Learning(ICCV 2023)[paper]
- When Prompt-based Incremental Learning Does Not Meet Strong Pretraining(ICCV 2023)[paper]
- Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision(ICCV 2023)[paper]
- Dynamic Residual Classifier for Class Incremental Learning(ICCV 2023)[paper]
- Audio-Visual Class-Incremental Learning(ICCV 2023)[paper]
- First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning(ICCV 2023)[paper]
- Self-Organizing Pathway Expansion for Non-Exemplar Class-Incremental Learning(ICCV 2023)[paper]
- Heterogeneous Forgetting Compensation for Class-Incremental Learning(ICCV 2023)[paper]
- Masked Autoencoders are Efficient Class Incremental Learners(ICCV 2023)[paper]
- Knowledge Restore and Transfer for Multi-Label Class-Incremental Learning(ICCV 2023)[paper]
- Space-time Prompting for Video Class-incremental Learning(ICCV 2023)[paper]
- CLNeRF: Continual Learning Meets NeRF(ICCV 2023)[paper]
- Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?(ICCV 2023)[paper]
- Exemplar-Free Continual Transformer with Convolutions(ICCV 2023)[paper]
- Self-Evolved Dynamic Expansion Model for Task-Free Continual Learning(ICCV 2023)[paper]
- Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision(ICCV 2023)