Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax(CVPR20)

时间 2020-12-26

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论文代码近几年，关于long-tailed或imbalanced problem在各个领域都受到持续关注，cvpr、iccv等会议也一直有关于相关问题的topic。最近，偶然读到了几篇关于解决该问题的比较有意思的文章，于是就简单记录一下。这篇文章BAGS是针对object detection中的long-tailed问题（LVIS 2019 challenge数据集），本人不是做cv的，但是实

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1. Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax(CVPR20)
2. Overcoming Classififier Imbalance for Long-tail Object Detection with Balanced Group Softmax 阅读笔记
3. CVPR 2020-Object Detection
4. Focal Loss for Dense Object Detection
5. 【Libra R-CNN】《Libra R-CNN: Towards Balanced Learning for Object Detection》
6. 【论文笔记】：Libra R-CNN: Towards Balanced Learning for Object Detection
7. 《Imbalance problems in object detection: A review》笔记
8. 目标检测--Focal Loss for Dense Object Detection
9. Metrics for object detection
10. Pillar-based Object Detection for Autonomous Driving
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1. Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax(CVPR20)
2. Overcoming Classififier Imbalance for Long-tail Object Detection with Balanced Group Softmax 阅读笔记
3. CVPR 2020-Object Detection
4. Focal Loss for Dense Object Detection
5. 【Libra R-CNN】《Libra R-CNN: Towards Balanced Learning for Object Detection》
6. 【论文笔记】：Libra R-CNN: Towards Balanced Learning for Object Detection
7. 《Imbalance problems in object detection: A review》笔记
8. 目标检测--Focal Loss for Dense Object Detection
9. Metrics for object detection
10. Pillar-based Object Detection for Autonomous Driving

>>更多相关文章<<