RetinaNet

Focal loss for dense object detection addressing class imbalance

FocalLoss

Addresses class imbalance in anchor-based detection (most anchors contain no object).

Key Points

  • Proposed: Focal loss — as $\gamma$ increases, easy sample weight decreases
  • Backbone: ResNet for powerful feature extraction
  • Multi-scale prediction
  • 9 anchors per level, each with classification and regression target