Good NEWS ! We have released the all the codes. Please refer to the project Hard-Aware-Deeply-Cascaded-Embedding_release
Yuan Y, Yang K, Zhang C. Hard-Aware Deeply Cascaded Embedding[J]. arXiv preprint arXiv:1611.05720, 2016.
This is the raw code for our work submitted to cvpr-2017. we will release the complete version in the future.(include the testing code). Here you can find all the training details in our implementation.
training data sample method :
cars-196 : random sample 10 classes (each with 10 images) as a mini-batch
cub-bird : random sample 10 classes (each with 10 images) as a mini-batch
stanford-online-products : random sample 2 big classes, then sample 10 classes in each big class. (each class only have small number of images)
deep-fashion : randome sample 2 big classes, then sample 10 classes in each big class.
we will release the sample method code as soon as possile.