Deepfake Creation and Detection Using Cycle GANs Deep learning has been successfully applied to a variety of complex problems, ranging from big data analytics to computer vision and human-level control, using Cycle GANs. However, advances in deep learning have also been used to develop software that can cause threats to privacy, democracy, and national security. Deepfake is a popular technique based on artificial intelligence for image synthesis. As it can produce images without paired training data, it is more powerful than traditional image-to-image translation. Deepfake algorithms can create fake images and videos that humans cannot distinguish from authentic ones.
Generative deep learning algorithms have progressed to a point where it is difficult to tell the difference between what is real and what is fake. This technology has creative and productive applications. For example, realistic video dubbing of foreign films, education through the reanimation of historical figures, and virtually trying on clothes while shopping. There are also numerous online communities devoted to creating deepfake memes for entertainment, such as music videos portraying the face of actors.
Project link: https://github.com/Charan1kh/Final-Year-Project