Long-tail Recognition via Compositional Knowledge Transfer-Reference-Cited by-同舟云学术

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Long-tail Recognition via Compositional Knowledge Transfer

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

Parisot Sarah¹,Esperanca Pedro M.¹,McDonagh Steven¹,Madarasz Tamas J.¹,Yang Yongxin¹,Li Zhenguo¹

Affiliation:

1. Huawei Noah's Ark Lab

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878751.pdf?arnumber=9878751

Reference33 articles.

1. BBN: Bilateral-Branch Network With Cumulative Learning for Long-Tailed Visual Recognition

2. Improving Calibration for Long-Tailed Recognition

3. Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

4. Dynamic Few-Shot Visual Learning Without Forgetting

Cited by 18 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. Mitigating biases in long-tailed recognition via semantic-guided feature transfer;Neurocomputing;2024-07

2. Compositional Servoing by Recombining Demonstrations;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. ProAug: Prototype-Based Augmentation for Long-Tailed Image Classification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. Rectify representation bias in vision-language models for long-tailed recognition;Neural Networks;2024-04

5. Center-Wise Feature Consistency Learning for Long-Tailed Remote Sensing Object Recognition;IEEE Transactions on Geoscience and Remote Sensing;2024

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