Cross-Scale Query-Support Alignment Approach for Small Object Detection in the Few-Shot Regime
Author:
Affiliation:
1. Université Sorbonne Paris Nord COSE,L2TI
2. Université Sorbonne Paris Nord,L2TI
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10221937/10221892/10222181.pdf?arnumber=10222181
Reference18 articles.
1. Prototypical networks for few-shot learning;snell;Advances in neural information processing systems,2017
2. Frustratingly simple few-shot object detection;wang;International Conference on Machine Learning (ICML),2020
3. RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection
4. Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images
5. LSTD: A Low-Shot Transfer Detector for Object Detection
Cited by 1 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. Improving Few-Shot and Cross-Domain Object Detection on Aerial Images with a Diffusion-Based Detector;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
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