TensorFlow Object Detection API - what do the losses mean in the object detection api?

Question

What do each for the following losses mean? (in the TensorFlow Object detection API, while training FasterRCNN based models)

Loss/BoxClassifierLoss/classification_lo

Answer 1

There are four losses that you will encounter if you are using the faster rcnn network

1.RPN LOSS/LOCALIZATION LOSS If we see the architecture of faster rcnn we will be having the cnn for getting the regoin proposals. For getting the region proposals from the feature map we have the loss functions . This is the localization loss for bounding boxes for the anchors generated.'

2.RPN LOSS/OBJECTNESS LOSS This is also when we are extracting the region proposals whether the object is present in the anchorbox or not.

3.BOX_CLASSIFIERLOSS/CLASSIFICATION_LOSS This is at the final layer to which class the object belongs to whether dog or cat??

4.BOX_CLASSIFIERLOSS/LOCALIZATION_LOSS This is also at the final layer for the bounding boxes of the object. (coordinates for dog and cat)