Reconciling Object-Level and Global-Level Objectives for Long-Tail Detection
Author:
Affiliation:
1. Chinese Academy of Sciences,Institute of Automation,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377973.pdf?arnumber=10377973
Reference56 articles.
1. Long-Tailed Instance Segmentation Using Gumbel Optimized Loss
2. Learning imbalanced datasets with label-distribution-aware margin loss;Cao;Advances in neural information processing systems,2019
3. Image-level or object-level? a tale of two resampling strategies for long-tailed detection;Chang
4. Towards Accurate One-Stage Object Detection With AP-Loss
5. AP-Loss for Accurate One-Stage 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. Foreground and Background Separate Adaptive Equilibrium Gradients Loss for Long-Tail Object Detection;Lecture Notes in Computer Science;2024
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