Libra R-CNN
Libra R-CNN
**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](https://paperswithcode.com/method/balanced-feature-pyramid), and [balanced L1 loss](https://paperswithcode.com/method/balanced-l1-loss), respectively for reducing the imbalance at sample, feature, and objective level.
Libra R-CNN: Towards Balanced Learning for Object Detection
https://paperswithcode.com/paper/libra-r-cnn-towards-balanced-learning-for
Libra R-CNN: Towards Balanced Learning for Object Detection