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Created: 2021-04-07T06:05:38.000Z (over 3 years ago)
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- Readme: README.md
Awesome Lists containing this project

awesome-ai-list-guide - Awesome_Continual-Lifelong-Incremental_learning - Lifelong-Incremental learning (Others)
README

        # Awesome Continual-Lifelong-Incremental learning

## Survey

-  Online Continual Learning in Image Classification: An Empirical Survey (**arXiv 2020**) [[paper](https://arxiv.org/abs/2101.10423)] [[code](https://github.com/RaptorMai/online-continual-learning)]

-  Continual Lifelong Learning in Natural Language Processing: A Survey (**COLING 2020**) [[paper](https://www.aclweb.org/anthology/2020.coling-main.574/)]

-  Class-incremental learning: survey and performance evaluation (**arXiv 2020**) [[paper](https://arxiv.org/abs/2010.15277)] [[code](https://github.com/mmasana/FACIL)]

-  A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks (**Neural Networks**) [[paper](https://arxiv.org/abs/2011.01844)] [[code](https://github.com/EdenBelouadah/class-incremental-learning/tree/master/cil)]

-  A continual learning survey: Defying forgetting in classification tasks (**TPAMI 2021**) [[paper]](https://ieeexplore.ieee.org/abstract/document/9349197) [[arxiv](https://arxiv.org/pdf/1909.08383.pdf)]

-  Continual Lifelong Learning with Neural Networks: A Review

 (**Neural Networks**) [[paper](https://arxiv.org/abs/1802.07569)]

## Papers

### 2021

-  IIRC: Incremental Implicitly-Refined Classification (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2012.12477)]

-  Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning (**CVPR, 2021**)

-  Prototype Augmentation and Self-Supervision for Incremental Learning (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.14898)]

-  SceneGraphFusion: Incremental 3D Scene Graph Prediction From RGB-D Sequences (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.14898)]

-  Continual Adaptation of Visual Representations via Domain Randomization and Meta-Learning 

(**CVPR, 2021**) [[paper](https://arxiv.org/abs/2012.04324)]

-  Image De-Raining via Continual Learning (**CVPR, 2021**)

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

(**CVPR, 2021**) [[paper](https://arxiv.org/abs/2101.00407)]

-  Layerwise Optimization by Gradient Decomposition for Continual Learning (**CVPR, 2021**)

-  Few-Shot Incremental Learning With Continually Evolved Classifiers (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2104.03047)]

-  Continual Learning via Bit-Level Information Preserving (**CVPR, 2021**) [[paper](https://arxiv.org/pdf/2105.04444.pdf)]

-  Learning the Superpixel in a Non-Iterative and Lifelong Manner (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.10681)]

-  Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation 

(**CVPR, 2021**) [[paper](https://www2.cs.sfu.ca/~mori/research/papers/zhai-cvpr21.pdf)]

-  Lifelong Person Re-Identification via Adaptive Knowledge Accumulation (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.12462)]

-  Incremental Learning via Rate Reduction (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2011.14593)]

-  Incremental Few-Shot Instance Segmentation (**CVPR, 2021**)

-  On Learning the Geodesic Path for Incremental Learning (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2104.08572)]

-  Adaptive Aggregation Networks for Class-Incremental Learning 

(**CVPR, 2021**) [[paper](https://arxiv.org/abs/2010.05063)] 

-  Efficient Feature Transformations for Discriminative and Generative Continual Learning 

(**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.13558)] 

-  Rectification-based Knowledge Retention for Continual Learning (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.16597)] 

-  DER: Dynamically Expandable Representation for Class Incremental Learning 

(**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.16788)] 

-  Rainbow Memory: Continual Learning with a Memory of Diverse Samples 

(**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.17230)] 

-  Training Networks in Null Space of Feature Covariance for Continual Learning

 (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.07113)] 

-  Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning

 (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.04059)] 

-  PLOP: Learning without Forgetting for Continual Semantic Segmentation

 (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2011.11390)] 

-  Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations

 (**CVPR, 2021**) [[paper](https://arxiv.org/abs/2103.06342)] 

-  Gradient Projection Memory for Continual Learning (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=3AOj0RCNC2)]

-  Graph-Based Continual Learning (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=HHSEKOnPvaO)]

-  Wandering within a world: Online contextualized few-shot learning 

(**ICLR, 2021**) [[paper](https://openreview.net/pdf/798a88cd0aefedd9aab888bc91f17fb86841e232.pdf)]

-  EEC: Learning to Encode and Regenerate Images for Continual Learning (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=lWaz5a9lcFU)]

-  Continual learning in recurrent neural networks (**ICLR, 2021**) [[paper](https://arxiv.org/abs/2006.12109)]

-  Linear Mode Connectivity in Multitask and Continual Learning (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=Fmg_fQYUejf)] 

-  Contextual Transformation Networks for Online Continual Learning (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=zx_uX-BO7CH)] 

-  Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting 

(**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=tHgJoMfy6nI)] 

-  Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning 

(**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=LXMSvPmsm0g)] 

-  Generalized Variational Continual Learning

(**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=_IM-AfFhna9)] 

-  CPR: Classifier-Projection Regularization for Continual Learning

 (**ICLR, 2021**) [[paper](https://arxiv.org/abs/2006.07326)] 

-  Incremental few-shot learning via vector quantization in deep embedded space

 (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=3SV-ZePhnZM)] 

-  Learning Structural Edits via Incremental Tree Transformations

 (**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=v9hAX77--cZ)] 

-  Reset-Free Lifelong Learning with Skill-Space Planning 

(**ICLR, 2021**) [[paper](https://openreview.net/pdf?id=HIGSa_3kOx3)]

-  Lifelong Learning of Compositional Structures (**ICLR, 2021**) [[paper](https://arxiv.org/abs/2007.07732)]

-  Lifelong Zero-Shot Learning(**IJCAI, 2021**)  [[paper](https://www.ijcai.org/proceedings/2020/77)] 

-  Online Class-Incremental Continual Learning with Adversarial Shapley Value(**AAAI, 2021**) [[paper](https://arxiv.org/abs/2009.00093)] [[code](https://github.com/RaptorMai/online-continual-learning)]

-  Lifelong and Continual Learning Dialogue Systems: Learning during Conversation(**AAAI, 2021**)  [[paper](https://www.cs.uic.edu/~liub/publications/LINC_paper_AAAI_2021_camera_ready.pdf)] 

-  Continual learning for named entity recognition(**AAAI, 2021**) [[paper](https://www.amazon.science/publications/continual-learning-for-named-entity-recognition)] 

-  Using Hindsight to Anchor Past Knowledge in Continual Learning(**AAAI, 2021**) [[paper](https://arxiv.org/abs/2002.08165)] 

-  Curriculum-Meta Learning for Order-Robust Continual Relation Extraction(**AAAI, 2021**) [[paper](https://arxiv.org/abs/2101.01926)] 

-  Continual Learning by Using Information of Each Class Holistically(**AAAI, 2021**) [[paper](https://www.cs.uic.edu/~liub/publications/AAAI2021_PCL.pdf)] 

-  Gradient Regularized Contrastive Learning for Continual Domain Adaptation(**AAAI, 2021**) [[paper](https://arxiv.org/abs/2007.12942)] 

-  Unsupervised Model Adaptation for Continual Semantic Segmentation(**AAAI, 2021**) [[paper](https://arxiv.org/abs/2009.12518)] 

-  A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation(**AAAI, 2021**) [[paper](https://www.aaai.org/AAAI21Papers/AAAI-2989.ZhengE.pdf)] 

-  Do Not Forget to Attend to Uncertainty While Mitigating Catastrophic Forgetting(**WACV, 2021**) [[paper](https://openaccess.thecvf.com/content/WACV2021/html/Kurmi_Do_Not_Forget_to_Attend_to_Uncertainty_While_Mitigating_Catastrophic_WACV_2021_paper.html)] 

### 2020

-  Continual Learning for Natural Language Generation in Task-oriented Dialog Systems(**EMNLP, 2020**) [[paper](https://arxiv.org/abs/2010.00910)] 

-  Distill and Replay for Continual Language Learning(**COLING, 2020**) [[paper](https://www.aclweb.org/anthology/2020.coling-main.318.pdf)] 

-  Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks (**NeurIPS2020**) [[paper](https://proceedings.neurips.cc/paper/2020/file/d7488039246a405baf6a7cbc3613a56f-Paper.pdf)] [[code](https://github.com/ZixuanKe/CAT)]

-  Meta-Consolidation for Continual Learning (**NeurIPS2020**) [[paper](https://arxiv.org/abs/2010.00352?context=cs)] 

-  Understanding the Role of Training Regimes in Continual Learning (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2006.06958.pdf)] 

-  Continual Learning with Node-Importance based Adaptive Group Sparse Regularization (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2003.13726.pdf)] 

-  Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2003.05856.pdf)] 

-  Coresets via Bilevel Optimization for Continual Learning and Streaming (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2006.03875.pdf)] 

-  RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2007.06271.pdf)] 

-  Continual Deep Learning by Functional Regularisation of Memorable Past (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2004.14070.pdf)] 

-  Dark Experience for General Continual Learning: a Strong, Simple Baseline (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2004.07211.pdf)]  [[code](https://github.com/aimagelab/mammoth)]

-  GAN Memory with No Forgetting (**NeurIPS2020**) [[paper](https://arxiv.org/pdf/2006.07543.pdf)] 

-  Calibrating CNNs for Lifelong Learning (**NeurIPS2020**) [[paper](http://people.ee.duke.edu/~lcarin/Final_Calibration_Incremental_Learning_NeurIPS_2020.pdf)] 

-  ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation(**RecSys, 2020**) [[paper](https://arxiv.org/abs/2007.12000)] 

-  Initial Classifier Weights Replay for Memoryless Class Incremental Learning (**BMVC2020**) [[paper](https://arxiv.org/pdf/2008.13710.pdf)] 

-  Adversarial Continual Learning (**ECCV2020**) [[paper](https://arxiv.org/abs/2003.09553)]  [[code](https://github.com/facebookresearch/Adversarial-Continual-Learning)]

-  REMIND Your Neural Network to Prevent Catastrophic Forgetting (**ECCV2020**) [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530460.pdf)]  [[code](https://github.com/tyler-hayes/REMIND)]

-  Incremental Meta-Learning via Indirect Discriminant Alignment (**ECCV2020**) [[paper](https://arxiv.org/abs/2002.04162)]

-  Memory-Efficient Incremental Learning Through Feature Adaptation (**ECCV2020**) [[paper](https://arxiv.org/abs/2004.00713)]

-  PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning (**ECCV2020**) [[paper](https://arxiv.org/abs/2004.13513)] [[code](https://github.com/arthurdouillard/incremental_learning.pytorch)]

-  Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference (**ECCV2020**) [[paper](https://arxiv.org/abs/2007.12540)]

-  Learning latent representions across multiple data domains using Lifelong VAEGAN (**ECCV2020**) [[paper](https://arxiv.org/abs/2007.10221)]

-  Online Continual Learning under Extreme Memory Constraints    (**ECCV2020**) [[paper](https://arxiv.org/abs/2008.01510)]

-  Class-Incremental Domain Adaptation (**ECCV2020**) [[paper](https://arxiv.org/abs/2008.01389)]

-  More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning (**ECCV2020**) [[paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123710698.pdf)]

-  Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation (**ECCV2020**) [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123660392.pdf)]

-  GDumb: A Simple Approach that Questions Our Progress in Continual Learning     (**ECCV2020**) [[paper](http://www.robots.ox.ac.uk/~tvg/publications/2020/gdumb.pdf)]

-  Imbalanced Continual Learning with Partitioning Reservoir Sampling     (**ECCV2020**) [[paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580409.pdf)]

-  Topology-Preserving Class-Incremental Learning (**ECCV2020**) [[paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123640256.pdf)]

-  GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems (**CIKM2020**) [[paper](https://arxiv.org/abs/2008.13517)]

-  OvA-INN: Continual Learning with Invertible Neural Networks (**IJCNN2020**) [[paper](https://arxiv.org/abs/2006.13772)]

-  XtarNet: Learning to Extract Task-Adaptive Representation

for Incremental Few-Shot Learning (**ICLM2020**) [[paper](https://arxiv.org/pdf/2003.08561.pdf)]

-  Optimal Continual Learning has Perfect Memory and is NP-HARD (**ICML2020**) [[paper](https://arxiv.org/pdf/2006.05188.pdf)]

-  Neural Topic Modeling with Continual Lifelong Learning (**ICML2020**) [[paper](https://arxiv.org/pdf/2006.10909.pdf)]

-  Continual Learning with Knowledge Transfer for Sentiment Classification (**ECML-PKDD2020**) [[paper](https://www.cs.uic.edu/~liub/publications/ECML-PKDD-2020.pdf)] [[code](https://github.com/ZixuanKe/LifelongSentClass)]

-  Semantic Drift Compensation for Class-Incremental Learning (**CVPR2020**) [[paper](https://arxiv.org/pdf/2004.00440.pdf)] [[code](https://github.com/yulu0724/SDC-IL)]

-  Few-Shot Class-Incremental Learning (**CVPR2020**) [[paper](https://arxiv.org/pdf/2004.10956.pdf)]

-  Modeling the Background for Incremental Learning in Semantic Segmentation (**CVPR2020**) [[paper](https://arxiv.org/pdf/2002.00718.pdf)]

-  Incremental Few-Shot Object Detection (**CVPR2020**) [[paper](https://arxiv.org/pdf/2003.04668.pdf)]

-  Incremental Learning In Online Scenario (**CVPR2020**) [[paper](https://arxiv.org/pdf/2003.13191.pdf)]

-  Maintaining Discrimination and Fairness in Class Incremental Learning (**CVPR2020**) [[paper](https://arxiv.org/pdf/1911.07053.pdf)]

-  Conditional Channel Gated Networks for Task-Aware Continual Learning (**CVPR2020**) [[paper](https://arxiv.org/pdf/2004.00070.pdf)]

-  Continual Learning with Extended Kronecker-factored Approximate Curvature

 (**CVPR2020**) [[paper](https://arxiv.org/abs/2004.07507)]

-  iTAML : An Incremental Task-Agnostic Meta-learning Approach (**CVPR2020**) [[paper](https://arxiv.org/pdf/2003.11652.pdf)] [[code](https://github.com/brjathu/iTAML)]

-  Mnemonics Training: Multi-Class Incremental Learning without Forgetting (**CVPR2020**) [[paper](https://arxiv.org/pdf/2002.10211.pdf)] [[code](https://github.com/yaoyao-liu/mnemonics)]

-  ScaIL: Classifier Weights Scaling for Class Incremental Learning (**WACV2020**) [[paper](https://arxiv.org/abs/2001.05755)]

-  Accepted papers(**ICLR2020**) [[paper](https://docs.google.com/presentation/d/17s5Y8N9dypH-59tuwKaCp80NYBxTmtT6V-zOFlsH-SA/edit?usp=sharing)]

-  Brain-inspired replay for continual learning with artificial neural networks (**Natrue Communications 2020**) [[paper](https://www.nature.com/articles/s41467-020-17866-2)] [[code](https://github.com/GMvandeVen/brain-inspired-replay)]

### 2019

-  Compacting, Picking and Growing for Unforgetting Continual Learning (**NeurIPS2019**)[[paper](https://papers.nips.cc/paper/9518-compacting-picking-and-growing-for-unforgetting-continual-learning.pdf)][[code](https://github.com/ivclab/CPG)]

-  Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning (**ICMR2019**) [[paper](https://dl.acm.org/doi/10.1145/3323873.3325053)][[code](https://github.com/ivclab/PAE)]

-  Towards Training Recurrent Neural Networks for Lifelong Learning (**Neural Computation 2019**) [[paper](https://arxiv.org/pdf/1811.07017.pdf)]

-  Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay  (**IJCAI2019**) [[paper]](https://www.ijcai.org/Proceedings/2019/0463.pdf)

-  IL2M: Class Incremental Learning With Dual Memory

 (**ICCV2019**) [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Belouadah_IL2M_Class_Incremental_Learning_With_Dual_Memory_ICCV_2019_paper.pdf)]

-  Incremental Learning Using Conditional Adversarial Networks

 (**ICCV2019**) [[paper](http://openaccess.thecvf.com/content_ICCV_2019/html/Xiang_Incremental_Learning_Using_Conditional_Adversarial_Networks_ICCV_2019_paper.html)]

-  Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability (**KDD2019**) [[paper](http://www.lamda.nju.edu.cn/yangy/KDD19.pdf)]

-  Random Path Selection for Incremental Learning (**NeurIPS2019**) [[paper](https://arxiv.org/pdf/1906.01120.pdf)]

-  Online Continual Learning with Maximal Interfered Retrieval (**NeurIPS2019**) [[paper](http://papers.neurips.cc/paper/9357-online-continual-learning-with-maximal-interfered-retrieval)]

-  Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild (**ICCV2019**) [[paper](https://arxiv.org/pdf/1903.12648.pdf)]

-  Continual Learning by Asymmetric Loss Approximation

with Single-Side Overestimation (**ICCV2019**) [[paper](https://arxiv.org/pdf/1908.02984.pdf)]

-  Lifelong GAN: Continual Learning for Conditional Image Generation (**ICCV2019**) [[paper](https://arxiv.org/pdf/1907.10107.pdf)]

-  Continual learning of context-dependent processing in neural networks (**Nature Machine Intelligence 2019**) [[paper](https://rdcu.be/bOaa3)] [[code](https://github.com/beijixiong3510/OWM)] 

-  Large Scale Incremental Learning (**CVPR2019**) [[paper](https://arxiv.org/abs/1905.13260)] [[code](https://github.com/wuyuebupt/LargeScaleIncrementalLearning)]

-  Learning a Unified Classifier Incrementally via Rebalancing (**CVPR2019**) [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Hou_Learning_a_Unified_Classifier_Incrementally_via_Rebalancing_CVPR_2019_paper.pdf)] [[code](https://github.com/hshustc/CVPR19_Incremental_Learning)]

-  Learning Without Memorizing (**CVPR2019**) [[paper](https://arxiv.org/pdf/1811.08051.pdf)] 

-  Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (**CVPR2019**) [[paper](https://arxiv.org/abs/1904.03137)] 

-  Task-Free Continual Learning (**CVPR2019**) [[paper](https://arxiv.org/pdf/1812.03596.pdf)]

-  Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting (**ICML2019**) [[paper](https://arxiv.org/abs/1904.00310)]

-  Efficient Lifelong Learning with A-GEM (**ICLR2019**) [[paper](https://openreview.net/forum?id=Hkf2_sC5FX)] [[code](https://github.com/facebookresearch/agem)]

-  Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference (**ICLR2019**) [[paper](https://openreview.net/forum?id=B1gTShAct7)] [[code](https://github.com/mattriemer/mer)]

-  Overcoming Catastrophic Forgetting via Model Adaptation (**ICLR2019**) [[paper](https://openreview.net/forum?id=ryGvcoA5YX)] 

-  A comprehensive, application-oriented study of catastrophic forgetting in DNNs (**ICLR2019**) [[paper](https://openreview.net/forum?id=BkloRs0qK7)] 

### 2018

-  Memory Replay GANs: learning to generate images from new categories without forgetting

 (**NIPS2018**) [[paper](https://arxiv.org/abs/1809.02058)] [[code](https://github.com/WuChenshen/MeRGAN)]

 -  Reinforced Continual Learning (**NIPS2018**) [[paper](http://papers.nips.cc/paper/7369-reinforced-continual-learning.pdf)] [[code](https://github.com/xujinfan/Reinforced-Continual-Learning)]

 -  Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting (**NIPS2018**) [[paper](http://papers.nips.cc/paper/7631-online-structured-laplace-approximations-for-overcoming-catastrophic-forgetting.pdf)]

-  Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting (R-EWC) (**ICPR2018**) [[paper](https://arxiv.org/abs/1802.02950)] [[code](https://github.com/xialeiliu/RotateNetworks)]

-  Exemplar-Supported Generative Reproduction for Class Incremental Learning  (**BMVC2018**) [[paper](http://bmvc2018.org/contents/papers/0325.pdf)] [[code](https://github.com/TonyPod/ESGR)]

-  End-to-End Incremental Learning (**ECCV2018**) [[paper](https://arxiv.org/abs/1807.09536)][[code](https://github.com/fmcp/EndToEndIncrementalLearning)]

-  Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence (**ECCV2018**)[[paper](http://arxiv-export-lb.library.cornell.edu/abs/1801.10112)] 

-  Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights (**ECCV2018**) [[paper](https://arxiv.org/abs/1801.06519)] [[code](https://github.com/arunmallya/piggyback)]

 -  Memory Aware Synapses: Learning what (not) to forget (**ECCV2018**) [[paper](https://arxiv.org/abs/1711.09601)] [[code](https://github.com/rahafaljundi/MAS-Memory-Aware-Synapses)]

  -  Lifelong Learning via Progressive Distillation and Retrospection (**ECCV2018**) [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Saihui_Hou_Progressive_Lifelong_Learning_ECCV_2018_paper.pdf)] 

-  PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning (**CVPR2018**) [[paper](https://arxiv.org/abs/1711.05769)] [[code](https://github.com/arunmallya/packnet)]

-  Overcoming Catastrophic Forgetting with Hard Attention to the Task (**ICML2018**) [[paper](http://proceedings.mlr.press/v80/serra18a.html)] [[code](https://github.com/joansj/hat)]

-  Lifelong Learning with Dynamically Expandable Networks (**ICLR2018**) [[paper](https://openreview.net/forum?id=Sk7KsfW0-)] 

-  FearNet: Brain-Inspired Model for Incremental Learning (**ICLR2018**) [[paper](https://openreview.net/forum?id=SJ1Xmf-Rb)] 

### 2017

-  Incremental Learning of Object Detectors Without Catastrophic Forgetting

 (**ICCV2017**) [[paper](http://openaccess.thecvf.com/content_iccv_2017/html/Shmelkov_Incremental_Learning_of_ICCV_2017_paper.html)] 

-  Overcoming catastrophic forgetting in neural networks (EWC) (**PNAS2017**) [[paper](https://arxiv.org/abs/1612.00796)] [[code](https://github.com/ariseff/overcoming-catastrophic)] [[code](https://github.com/stokesj/EWC)]

-  Continual Learning Through Synaptic Intelligence (**ICML2017**) [[paper](http://proceedings.mlr.press/v70/zenke17a.html)] [[code](https://github.com/ganguli-lab/pathint)]

-  Gradient Episodic Memory for Continual Learning (**NIPS2017**) [[paper](https://arxiv.org/abs/1706.08840)] [[code](https://github.com/facebookresearch/GradientEpisodicMemory)]

-  iCaRL: Incremental Classifier and Representation Learning (**CVPR2017**) [[paper](https://arxiv.org/abs/1611.07725)] [[code](https://github.com/srebuffi/iCaRL)]

-  Continual Learning with Deep Generative Replay (**NIPS2017**) [[paper](https://arxiv.org/abs/1705.08690)] [[code](https://github.com/kuc2477/pytorch-deep-generative-replay)]

-  Overcoming Catastrophic Forgetting by Incremental Moment Matching (**NIPS2017**) [[paper](https://arxiv.org/abs/1703.08475)] [[code](https://github.com/btjhjeon/IMM_tensorflow)]

-  Expert Gate: Lifelong Learning with a Network of Experts (**CVPR2017**) [[paper](https://arxiv.org/abs/1611.06194)] 

-  Encoder Based Lifelong Learning (**ICCV2017**) [[paper](https://arxiv.org/abs/1704.01920)] 

### 2016

-  Learning without forgetting (**ECCV2016**) [[paper](https://link.springer.com/chapter/10.1007/978-3-319-46493-0_37)] [[code](https://github.com/lizhitwo/LearningWithoutForgetting)]

## ContinualAI wiki

#### [An Open Community of Researchers and Enthusiasts on Continual/Lifelong Learning for AI](https://www.continualai.org/)

## Workshops

#### [4th Lifelong Learning Workshop at ICML 2020](https://lifelongml.github.io/)

#### [Workshop on Continual Learning at ICML 2020](https://icml.cc/Conferences/2020/Schedule?showEvent=5743)

#### [Continual Learning in Computer Vision Workshop CVPR 2020](https://sites.google.com/view/clvision2020/overview)

#### [Continual learning workshop NeurIPS 2018](https://sites.google.com/view/continual2018/home?authuser=0)

## Challenges or Competitions

#### [1st Lifelong Learning for Machine Translation Shared Task at WMT20 (EMNLP 2020)](http://www.statmt.org/wmt20/lifelong-learning-task.html)

#### [Continual Learning in Computer Vision Challenge CVPR 2020](https://sites.google.com/view/clvision2020/challenge?authuser=0)

#### [Lifelong Robotic Vision Challenge IROS 2019](https://lifelong-robotic-vision.github.io)

## Acknowledgement

The content is mainly based on [Awesome_Continual-Lifelong-Incremental_learning](https://github.com/chengsilin/Awesome_Continual-Lifelong-Incremental_learning)