VFNet is short for VariFocalNet. This method of object detection was first released in 2008 and it scored 55.1 on the COCO test-dev benchmark, state-of-the-art at the time. There have since been other improvements.
The problem it solves is that when we’re training a model, we have a large number of possible options for objects detected in an image. What we need to do is rank these options in order of likelihood of being a correct bounding of a box.
It is based on and draws on the MMDetection model/toolbox. MMDetection is a Pytorch library for object detection. It is modular, allowing for greater customisability.