IoU-balanced Loss Functions for Single-stage Object Detection

Understand

Single-stage object detectors have been widely applied in computer vision applications due to their high efficiency.

• However, we find that the loss functions adopted by single-stage object detectors hurt the localization accuracy seriously.
• Firstly, the standard cross-entropy loss for classification is independent of the localization task and drives all the positive examples to learn as high classification scores as possible regardless of localization accuracy during training.
• As a result, there will be many detections that have high classification scores but low IoU or detections that have low classification scores but high IoU.