Few-Shot Class Incremental Learning Leveraging Self-Supervised Features

Author:

Ahmad Touqeer1,Dhamija Akshay Raj1,Cruz Steve1,Rabinowitz Ryan1,Li Chunchun1,Jafarzadeh Mohsen1,Boult Terrance E.1

Affiliation:

1. University of Colorado Colorado Springs,Vision and Security Technology Lab,Colorado Springs,CO,USA

Funder

Advanced Research Projects Agency

Publisher

IEEE

Reference63 articles.

1. Classincremental learning: survey and performance evaluation;masana,2020

2. An Appraisal of Incremental Learning Methods

3. Learning Multiple Layers of Features from Tiny Images;krizhevsky;Technical Report,2009

4. Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics

5. Memory-efficient incremental learning through feature adaptation;iscen;Eur Conf Comput Vis,2020

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1. An Analysis of Initial Training Strategies for Exemplar-Free Class-Incremental Learning;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

2. DyCR: A Dynamic Clustering and Recovering Network for Few-Shot Class-Incremental Learning;IEEE Transactions on Neural Networks and Learning Systems;2024

3. A survey on few-shot class-incremental learning;Neural Networks;2024-01

4. Gradient Guided Multiscale Feature Collaboration Networks for Few-Shot Class-Incremental Remote Sensing Scene Classification;IEEE Transactions on Geoscience and Remote Sensing;2024

5. Multimodal Parameter-Efficient Few-Shot Class Incremental Learning;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

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