Different IoU Losses for Faster and Accurate Object Detection

Learn Generalized IoU, Distance IoU, and Complete IoU Loss used in State of the art object detection algorithms

Object detection, which includes two sub-tasks: object classification and object localization.

Object Localization relies on a bounding box regression (BBR) module to localize objects.

Bounding Box Regression

Bounding-box regression is a popular technique in object detection algorithm used to predict target objects' location using rectangular bounding boxes. It aims to refine the location of a predicted bounding box.

Bounding box regression uses overlap area between the predicted bounding box and the ground truth bounding box referred to as Intersection over Union (IOU) based losses.

Intersection over Union

IoU loss only works when the predicted bounding boxes overlap with the ground truth box. IOU loss would not provide any moving gradient for non-overlapping cases.

The convergence speed of the IOU loss is slow.