SSD object detection - notitiam/ML-paper-notes GitHub Wiki

• Image classification vs Object detection vs Segmentation
• Two stage approaches:
  • Region proposal
    • e.g. Sliding window approach
  • Detection
  • R-CNN, Fast R-CNN, Faster R-CNN
  • Problems: Computationally expensive
• Single shot detectors: SSD, YOLO, YOLO v3 etc

Details:

• Multi scale feature map
• Default boxes and aspect ratios (Anchor boxes)
• Training:
  • choose feature map
  • location in feature map
  • associated ground truth box
  • train all boxes with IoU > 0.5
• hard negative mining: highest confidence loss (3:1, negative:positive)
• 11 priors per feature map cell, total of 1420 priors per image