Libra R-CNN

2000년 도입 · 논문 5편에서 사용

Libra R-CNN is an object detection model that seeks to achieve a balanced training procedure. The authors motivation is that training in past detectors has suffered from imbalance during the training process, which generally consists in three levels – sample level, feature level, and objective level. To mitigate the adverse effects, Libra R-CNN integrates three novel components: IoU-balanced sampling, balanced feature pyramid, and balanced L1 loss, respectively for reducing the imbalance at sample, feature, and objective level.

출처: Libra R-CNN: Towards Balanced Learning for Object Detection

소개 논문: Libra R-CNN: Towards Balanced Learning for Object Detection