Semantics-Driven Generative Replay for Few-Shot Class Incremental Learning-Reference-Cited by-同舟云学术

Semantics-Driven Generative Replay for Few-Shot Class Incremental Learning

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM International Conference on Multimedia
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Author:

Agarwal Aishwarya¹,Banerjee Biplab¹,Cuzzolin Fabio²,Chaudhuri Subhasis¹

Affiliation:

1. Indian Institute of Technology Bombay, Mumbai, India

2. Oxford Brookes University, Oxford, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3503161.3548160

Reference43 articles.

1. Adamu Ali-Gombe , Eyad Elyan , Yann Savoye , and Chrisina Jayne . 2018 . Few-shot Classifier GAN. In 2018 International Joint Conference on Neural Networks (IJCNN). 1--8. https://doi.org/10 .1109/IJCNN.2018.8489387 Adamu Ali-Gombe, Eyad Elyan, Yann Savoye, and Chrisina Jayne. 2018. Few-shot Classifier GAN. In 2018 International Joint Conference on Neural Networks (IJCNN). 1--8. https://doi.org/10.1109/IJCNN.2018.8489387

2. S Divakar Bhat Biplab Banerjee and Subhasis Chaudhuri. 2021. SemGIF: A Semantics Guided Incremental Few-shot Learning Framework with Generative Replay. (2021). S Divakar Bhat Biplab Banerjee and Subhasis Chaudhuri. 2021. SemGIF: A Semantics Guided Incremental Few-shot Learning Framework with Generative Replay. (2021).

3. Enriching Word Vectors with Subword Information

4. End-to-End Incremental Learning

5. Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence

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