Robust Optimization for Deep Regression

This is a MatConvNet implementation of the work:

Robust Optimization for Deep Regression Vasileios Belagiannis, Christian Rupprecht, Gustavo Carneiro, and Nassir Navab, International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015. Project, Arxiv.

There is an example of training a model using the robust loss. To train the example model, one have to:

1. Download the LSP dataset (fetchNprepareLSP.m in the data folder).
2. Run the script train_LSP_Model.m that is place in the keypoint-regressor folder.
3. To Evaluate a trained model, check the script cnn_eval.m in the keypoint-regressor.

There is also a trained model net-epoch-40.mat in the data folder.

MatConvNet beta-21 is included into the project.

PyTorch implmentation is comming soon.

Lisence: This code and MatConvNet are made available under the terms of the BSD license (see the COPYING file).