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adversarial-examples-in-pytorch

Pytorch code to generate adversarial examples on mnist and ImageNet data.

adversarial-steganography

aletheia

Image steganalysis using state-of-the-art machine learning techniques

anti-forensics-using-gan

Median Filtered Image Restoration and Anti-Forensics Using Adversarial Networks

awesome-image-steganography

blockwin10au

禁止Windows10系统自动更新

boundary-attack

Implementation of the Boundary Attack algorithm as described in Brendel, Wieland, Jonas Rauber, and Matthias Bethge. "Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models." arXiv preprint arXiv:1712.04248 (2017).

caffe

Caffe: a fast open framework for deep learning.

caffe-tensorflow

Caffe models in TensorFlow

caffe_deep_learning_for_steganalysis

caffe_gan

This project uses GAN to implement gray image colorization

calpa-net

cbow.tensorflow

cloacked-pixel

LSB steganography and detection

cnn-cbir

A simple achivement of CBIR based on CNN

cnn_cbir

cnn_cbir2

cnniqa

CVPR2014-Convolutional neural networks for no-reference image quality assessment

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

dcgan.caffe

A pure caffe-python implementation of DC-GAN

dcgan_model4steg

dcnn_ni_cg_forensic

Convert the original Caffe version to Pytorch version

densenet

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

design-patterns-for-humans-cn

🎉 Design patterns for humans 中文机翻版

dnn-watermark

Implementation of "Embedding Watermarks into Deep Neural Networks," in Proc. of ICMR'17.

dragan

A stable algorithm for GAN training

extract-subtitle

Subtitle extraction system for Smart Subtitles http://up.csail.mit.edu/other-pubs/chi2014-smartsubs.pdf

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

hill-python

Hill steganography in python

illustration2vec

A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.