SE-FewDet: Semantic-Enhanced Feature Generation and Prediction Refinement for Few-Shot Object Detection
Author:
Affiliation:
1. Zhejiang University of Technology,Zhejiang,China
Funder
Natural Science Foundation of Zhejiang Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650252.pdf?arnumber=10650252
Reference31 articles.
1. Few-Shot Object Detection with Fully Cross-Transformer
2. Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment
3. An Effective Crop-Paste Pipeline for Few-shot Object Detection
4. Generating Features with Increased Crop-Related Diversity for Few-Shot Object Detection
5. Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection
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