.. vim: set fileencoding=utf-8 : .. Tiago de Freitas Pereira ===================================== Idiap - Resnet V2/V1 - Casia Webface ===================================== Inspired by `**FaceNet** `_ we here at Idiap trained our own CNN using the Inception Resnet 2 architecture using Casia Webface database. In this `links `_ you can find the script that trains this neural network. To trigger this training it's necessary to use the `bob.learn.tensorflow `_ package and run the following command:: $ ./bin/jman submit --name CELEB-GRAY --queue gpu -- bob_tf_train_generic CASIA_inception_resnet_v2_center_loss.py Some quick details about this CNN (just as a mental note): - The hot encoded layer has 10574 neurons. - Faces were detected and croped to :math:`182 \times 182` using `MTCNN `_ face and landmark detector - The following data augmentation strategies were implemented: * Random crop to :math:`160 \times 160` * Random Flip * Images were normalized to have zero mean and standard deviation one - Learning rate of 0.1, 0.01, 0.001 - RMSPROP Optimizer - Batch size of 90