/Awesome-Incremental-Learning

Awesome Incremental Learning

Awesome Incremental Learning / Lifelong learning

Feel free to contact me if you find any interesting paper is missing.

ContinualAI wiki

An Open Community of Researchers and Enthusiasts on Continual/Lifelong Learning for AI

Workshops

Continual learning workshop NeurIPS 2018

4th Lifelong Learning Workshop at ICML 2020

Continual Learning in Computer Vision Workshop CVPR 2020

single-head v.s. multi-head; w exemplars or w/o exemplars

Being aware of different training and test settings.

Challenges or Competitions

Lifelong Robotic Vision Challenge IROS 2019

Continual Learning in Computer Vision Challenge CVPR 2020

Survey

  • Continual learning: A comparative study on how to defy forgetting in classification tasks (arXiv 2019) [paper]
  • Continual Lifelong Learning with Neural Networks: A Review (arXiv 2018) [paper]

Papers

2020

  • Semantic Drift Compensation for Class-Incremental Learning (CVPR2020) [paper] [code]
  • Few-Shot Class-Incremental Learning (CVPR2020) [paper]
  • Conditional Channel Gated Networks for Task-Aware Continual Learning (CVPR2020) [paper]
  • Continual Learning with Extended Kronecker-factored Approximate Curvature (CVPR2020) [paper]
  • iTAML : An Incremental Task-Agnostic Meta-learning Approach (CVPR2020) [paper] [code]
  • Mnemonics Training: Multi-Class Incremental Learning without Forgetting (CVPR2020) [paper] [code]
  • Accepted papers(ICLR2020) [paper]

2019

  • Compacting, Picking and Growing for Unforgetting Continual Learning (NeurIPS2019)[paper][code]
  • Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning (ICMR2019) [paper][code]
  • Towards Training Recurrent Neural Networks for Lifelong Learning (Neural Computation 2019) [paper]
  • IL2M: Class Incremental Learning With Dual Memory (ICCV2019) [paper]
  • Incremental Learning Using Conditional Adversarial Networks (ICCV2019) [paper]
  • Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability (KDD2019) [paper]
  • Random Path Selection for Incremental Learning (NeurIPS2019) [paper]
  • Online Continual Learning with Maximal Interfered Retrieval (NeurIPS2019) [paper]
  • Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild (ICCV2019) [paper]
  • Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation (ICCV2019) [paper]
  • Lifelong GAN: Continual Learning for Conditional Image Generation (ICCV2019) [paper]
  • Continual learning of context-dependent processing in neural networks (Nature Machine Intelligence 2019) [paper] [code]
  • Large Scale Incremental Learning (CVPR2019) [paper] [code]
  • Learning a Unified Classifier Incrementally via Rebalancing (CVPR2019) [paper] [code]
  • Learning Without Memorizing (CVPR2019) [paper]
  • Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (CVPR2019) [paper]
  • Task-Free Continual Learning (CVPR2019) [paper]
  • Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting (ICML2019) [paper]
  • Efficient Lifelong Learning with A-GEM (ICLR2019) [paper] [code]
  • Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference (ICLR2019) [paper] [code]
  • Overcoming Catastrophic Forgetting via Model Adaptation (ICLR2019) [paper]
  • A comprehensive, application-oriented study of catastrophic forgetting in DNNs (ICLR2019) [paper]
  • Incremental Learning Techniques for Semantic Segmentation (ICCVW2019) [paper] [code]

2018

  • Memory Replay GANs: learning to generate images from new categories without forgetting (NIPS2018) [paper] [code]
  • Reinforced Continual Learning (NIPS2018) [paper] [code]
  • Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting (NIPS2018) [paper]
  • Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting (R-EWC) (ICPR2018) [paper] [code]
  • Exemplar-Supported Generative Reproduction for Class Incremental Learning (BMVC2018) [paper] [code]
  • DeeSIL: Deep-Shallow Incremental Learning (ECCV2018) [paper]
  • End-to-End Incremental Learning (ECCV2018) [paper][code]
  • Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence (ECCV2018)[paper]
  • Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights (ECCV2018) [paper] [code]
  • Memory Aware Synapses: Learning what (not) to forget (ECCV2018) [paper] [code]
  • Lifelong Learning via Progressive Distillation and Retrospection (ECCV2018) [paper]
  • PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning (CVPR2018) [paper] [code]
  • Overcoming Catastrophic Forgetting with Hard Attention to the Task (ICML2018) [paper] [code]
  • Lifelong Learning with Dynamically Expandable Networks (ICLR2018) [paper]
  • FearNet: Brain-Inspired Model for Incremental Learning (ICLR2018) [paper]

2017

  • Incremental Learning of Object Detectors Without Catastrophic Forgetting (ICCV2017) [paper]
  • Overcoming catastrophic forgetting in neural networks (EWC) (PNAS2017) [paper] [code] [code]
  • Continual Learning Through Synaptic Intelligence (ICML2017) [paper] [code]
  • Gradient Episodic Memory for Continual Learning (NIPS2017) [paper] [code]
  • iCaRL: Incremental Classifier and Representation Learning (CVPR2017) [paper] [code]
  • Continual Learning with Deep Generative Replay (NIPS2017) [paper] [code]
  • Overcoming Catastrophic Forgetting by Incremental Moment Matching (NIPS2017) [paper] [code]
  • Expert Gate: Lifelong Learning with a Network of Experts (CVPR2017) [paper]
  • Encoder Based Lifelong Learning (ICCV2017) [paper]

2016

  • Learning without forgetting (ECCV2016) [paper] [code]