This directory contains reference code for the paper A General and Adaptive Robust Loss Function, Jonathan T. Barron CVPR, 2019
To use this code, include general.py or adaptive.py and call the loss
function. general.py implements the "general" form of the loss, which assumes
you are prepared to set and tune hyperparameters yourself, and adaptive.py
implements the "adaptive" form of the loss, which tries to adapt the
hyperparameters automatically and also includes support for imposing losses in
different image representations. The probability distribution underneath the
adaptive loss is implemented in distribution.py.
This code repository is shared with all of Google Research, so it's not very useful for reporting or tracking bugs. If you have any issues using this code, please do not open an issue, and instead just email [email protected].
If you use this code, please cite it:
@article{BarronCVPR2019,
Author = {Jonathan T. Barron},
Title = {A General and Adaptive Robust Loss Function},
Journal = {CVPR},
Year = {2019}
}