Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification-Reference-Cited by-同舟云学术

Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
Short-container-title:

Author:

Liu Yang¹,Zhang Weifeng¹,Xiang Chao¹,Zheng Tu¹,Cai Deng¹,He Xiaofei¹

Affiliation:

1. Zhejiang University,State Key Lab of CAD&CG

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878529.pdf?arnumber=9878529

Reference32 articles.

1. Learning with local and global consistency;dengyong;Advances in Neural Information Processing Systems 16,2003

2. Deepemd: Differentiable earth mover's distance for few-shot learning;zhang;ArXiv e-prints,2020

3. Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions

4. Meta-Learning With Differentiable Convex Optimization

5. Asymmetric distribution measure for few-shot learning;li;Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence,2021

Cited by 47 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Few-shot learning with long-tailed labels;Pattern Recognition;2024-12

2. AMMD: Attentive maximum mean discrepancy for few-shot image classification;Pattern Recognition;2024-11

3. Few-shot open-set recognition via pairwise discriminant aggregation;Neurocomputing;2024-10

4. Few-shot fault diagnosis of rolling bearing via mutual centralized learning combining simple and parameter-free attention;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2024-09-09

5. Bimodal semantic fusion prototypical network for few-shot classification;Information Fusion;2024-09