Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/jhairgallardo/awesome-continual-self-supervised-learning

List of papers that combine self-supervision and continual learning
https://github.com/jhairgallardo/awesome-continual-self-supervised-learning

List: awesome-continual-self-supervised-learning

continual-learning self-supervised-learning

Last synced: 16 days ago
JSON representation

List of papers that combine self-supervision and continual learning

Awesome Lists containing this project

README 

        
# Awesome Continual Self-Supervised Learning [![Awesome](https://jaywcjlove.github.io/sb/ico/awesome.svg)](https://github.com/sindresorhus/awesome)

List of papers that combine self-supervision and continual learning



## Papers

### 2024

- Evolve: Enhancing Unsupervised Continual Learning With Multiple Experts (**WACV 2024**) [[paper](https://openaccess.thecvf.com/content/WACV2024/html/Yu_Evolve_Enhancing_Unsupervised_Continual_Learning_With_Multiple_Experts_WACV_2024_paper.html)][[code](https://github.com/Orienfish/Evolve)]

- Integrating Present and Past in Unsupervised Continual Learning (**CoLLAs 2024**) [[paper](https://arxiv.org/abs/2404.19132)][[code](https://github.com/SkrighYZ/Osiris)]

- CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning (**ECCV 2024**) [[paper](https://arxiv.org/abs/2407.12188)][[code](https://github.com/ErumMushtaq/CroMo-Mixup)]

- Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning (**ICML 2024**) [[paper](https://arxiv.org/abs/2306.05101)][[code](https://github.com/csm9493/PNR)]

  

### 2023

- Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning (**arXiv 2023**) [[paper](https://arxiv.org/abs/2306.05101v1)]

- CoRaL: Continual Representation Learning for Overcoming Catastrophic Forgetting (**AAMAS 2023**) [[paper](https://dl.acm.org/doi/abs/10.5555/3545946.3598866)]

- Kaizen: Practical self-supervised continual learning with continual fine-tuning (**arXiv 2023**) [[paper](https://arxiv.org/abs/2303.17235)][[code](https://github.com/dr-bell/kaizen)]

- CSSL-MHTR: Continual Self-Supervised Learning for Scalable Multi-script Handwritten Text Recognition (**arXiv 2023**) [[paper](https://arxiv.org/abs/2303.09347)]

- Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing (**arXiv 2023**) [[paper](https://arxiv.org/abs/2303.07477)]

- Towards Label-Efficient Incremental Learning: A Survey (**arXiv 2023**) [[paper](https://arxiv.org/abs/2302.00353)]

- Are Labels Needed for Incremental Instance Learning? (**CVPRW 2023**) [[paper](https://arxiv.org/abs/2301.11417)]

- Continual Barlow Twins: continual self-supervised learning for remote sensing semantic segmentation (**arXiv 2023**) [[paper](https://arxiv.org/abs/2205.11319)]

- SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge (**CVPRW 2023**) [[paper](https://arxiv.org/abs/2208.11266)]



### 2022

- Grow and Merge: A Unified Framework for Continuous Categories Discovery (**NeurIPS 2022**) [[paper](https://arxiv.org/abs/2210.04174)]

- Beyond Supervised Continual Learning: a Review (**ESANN 2022**) [[paper](https://arxiv.org/abs/2208.14307)]

- How Well Does Self-Supervised Pre-Training Perform with Streaming Data? (**ICLR 2022**) [[paper](https://arxiv.org/abs/2104.12081)]

- Continual Contrastive Learning for Image Classification (**ICME 2022**) [[paper](https://arxiv.org/abs/2107.01776)]

- Task Agnostic Representation Consolidation: a Self-supervised based Continual Learning Approach (**CoLLAs 2022**) [[paper](https://arxiv.org/abs/2207.06267)] [[code](https://github.com/NeurAI-Lab/TARC)]

- Continually Learning Self-Supervised Representations with Projected Functional Regularization (**CVPR 2022**) [[paper](https://arxiv.org/abs/2112.15022)]

- Representational Continuity for Unsupervised Continual Learning (**ICLR 2022**) [[paper](https://arxiv.org/abs/2110.06976)] [[code](https://github.com/divyam3897/UCL)]

- Self-Supervised Models are Continual Learners (**CVPR 2022**) [[paper](https://arxiv.org/abs/2112.04215)] [[code](https://github.com/DonkeyShot21/cassle)]

- The Challenges of Continuous Self-Supervised Learning (**ECCV 2022**) [[paper](https://arxiv.org/abs/2203.12710)] [[code](https://github.com/senthilps8/continuous_ssl_problem)]

- MUSCLE: Multi-task Self-supervised Continual Learning to Pre-train Deep Models for X-Ray Images of Multiple Body Parts (**MICCAI 2022**) [[paper](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_15)]



### 2021

- Self-Supervised Class Incremental Learning (**arXiv 2021**) [[paper](https://arxiv.org/abs/2111.11208)]

- DualNet: Continual Learning, Fast and Slow (**NeurIPS 2021**) [[paper](https://arxiv.org/abs/2110.00175)] [[code](https://github.com/phquang/DualNet)]

- Co2L: Contrastive Continual Learning (**ICCV 2021**) [[paper](https://arxiv.org/abs/2106.14413)] [[code](https://github.com/chaht01/Co2L)]

- SPeCiaL: Self-Supervised Pretraining for Continual Learning (**IJCAI-W 2021**) [[paper](https://arxiv.org/abs/2106.09065)]

- Prototype Augmentation and Self-Supervision for Incremental Learning (**CVPR 2021**) [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhu_Prototype_Augmentation_and_Self-Supervision_for_Incremental_Learning_CVPR_2021_paper.pdf)]

- Self-Supervised Training Enhances Online Continual Learning (**BMVC 2021**) [[paper](https://arxiv.org/abs/2103.14010)]

- Reduce the Difficulty of Incremental Learning With Self-Supervised Learning (**2021**) [[paper](https://ieeexplore.ieee.org/document/9537773)]



### 2020

- Self-Supervised Learning Aided Class-Incremental Lifelong Learning (**arXiv 2020**) [[paper](https://arxiv.org/abs/2006.05882)]



### 2019

- Continual Unsupervised Representation Learning (**NeurIPS 2019**) [[paper](https://arxiv.org/abs/1910.14481)]