VariFocal Loss

VariFocal Loss is a loss function that is specifically designed for object detection tasks in computer vision. It is a modification of the standard cross-entropy loss function that takes into account the fact that objects can appear at different scales and locations within an image.

The VariFocal Loss function assigns different weights to the positive and negative examples based on their degree of difficulty. The difficulty is determined by the IoU (Intersection over Union) between the predicted bounding box and the ground truth bounding box. The harder examples are given more weight to ensure that the model focuses on learning from the more challenging examples.

VariFocal Loss has been shown to improve the performance of object detection models in comparison to other loss functions. It is particularly effective when dealing with small objects or objects that are partially occluded.