What do each for the following losses mean? (in the TensorFlow Object detection API, while training FasterRCNN based models)
Loss/BoxClassifierLoss/classification_loss/mul_1
Loss/BoxClassifierLoss/localization_loss/mul_1
Loss/RPNLoss/localization_loss/mul_1
Loss/RPNLoss/objectness_loss/mul_1
clone_loss_1
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.
来源：https://stackoverflow.com/questions/48111847/tensorflow-object-detection-api-what-do-the-losses-mean-in-the-object-detectio