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

The losses for the Region Proposal Network:

Loss/RPNLoss/localization_loss/mul_1: Localization Loss or the Loss of the Bounding Box regressor for the RPN

Loss/RPNLoss/objectness_loss/mul_1: Loss of the Classifier that classifies if a bounding box is an object of interest or background

The losses for the Final Classifier:

Loss/BoxClassifierLoss/classification_loss/mul_1: Loss for the classification of detected objects into various classes: Cat, Dog, Airplane etc

Loss/BoxClassifierLoss/localization_loss/mul_1: Localization Loss or the Loss of the Bounding Box regressor

clone_loss_1 is relevant only if you train on multiple GPUs: Tensorflow would create a clone of the model to train on each GPU and report the loss on each clone. If you are training the model on a single GPU/CPU, then you will just see clone_loss_1, which is the same as TotalLoss.

The other losses are as described in Rohit's answer.