Cross-Modal Learning with Adversarial Samples (NeurIPS2019)

Installation

• To install Tensorflow and Python:
  Tensorflow=1.12.0;
  Python=Python 3.6.8;

Step1:

• Creat /Flickr-25K/ to save Dataset;
  Download Img.h5, Img.h5, Lab.h5, and Mean.h5 from here and save to /Flickr-25K;
• Creat /model/ to save CNNF network;
  Download imagenet-vgg-f.mat from here;
• Creat /AttackHash_SSAH_Flickr/AdversarialSamples/ to save the learned Adversarial Samples;
• Creat /AttackHash_SSAH_Flickr/NoiseSamples/ to save the learned Perturbation;
• Creat /AttackHash_SSAH_Flickr/checkpoint/ to save checkpoint for tensorflow models;
• Creat /AttackHash_SSAH_Flickr/Savecode/ to save the learned hash codes;
• Creat AttackHash_SSAH_Flickr/LogText/ for a log print;

Step2:

• run demo_train_BasicModel.py to train a basic deep cross-modal hash network (SSAH_CVPR18);
• run demo_learn_AdversarialSampls.py to learn adversarial samples;
• run demo_AdversarialTraining.py to finetuning the basic model;