This is only the caffe implementation for the KL loss in the paper:
Bounding Box Regression with Uncertainty for Accurate Object Detection
@inproceedings{klloss, title={Bounding Box Regression with Uncertainty for Accurate Object Detection}, author={He, Yihui and Zhu, Chenchen and Wang, Jianren and Savvides, Marios and Zhang, Xiangyu }, booktitle={2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2019}, organization={IEEE} }
if you have three inputs (not include weights)
layer {
name: "loss_kl"
type: "KlLoss"
bottom: "coor"
bottom: "theta"
bottom: "label"
top: "kl_loss"
propagate_down: 1
propagate_down: 1
propagate_down: 0
loss_weight: 1
}
if you have four inputs (include weights)
layer {
name: "loss_kl"
type: "KlLoss"
bottom: "coor"
bottom: "theta"
bottom: "label"
bottom: "weight"
top: "kl_loss"
propagate_down: true
propagate_down: true
propagate_down: false
propagate_down: false
include {
phase: TRAIN
}
}