Merdeepfakes. Deepfakes represent a form of synthetic media generated through advanced artificial intelligence techniques, including deep learning, neural networks, and generative adversarial networks (GANs). They intricately blend existing images, videos, or audio with new elements, often resulting in hyper-realistic simulations.

Pull requests. This projects aims in detection of video deepfakes using deep learning techniques like RestNext and LSTM. We have achived deepfake detection by using transfer learning where the pretrained RestNext CNN is used to obtain a feature vector, further the LSTM layer is trained using the features. For more details follow the documentaion.

Merdeepfakes. This thread will be created every month and pinned at the top of the subreddit to help new users. As long as discussion and questions are safe for work in nature (Don't link to NSFW tutorials, materials as sidebar states) you can ask here without fear of ridicule for how simple or overly complicated the question may be.

A GAN is trained by pitting two neural networks against each other: one generates content and the other evaluates it, which creates increasingly realistic outputs through competition. In deepfake videos created by GAN models, manipulation is applied to specific parts of the footage, for example the mouth. This results in fakes like this one ...

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Guides and Tutorials. Learn how to create your own deepfakes from our guides and tutorials. Various guides of different deepfake apps, and techniques can be found and shared here. Learn from developers, and seasoned deepfake creators inside. 1.

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Deepfakes uses a special type of neural-network structure called an "autoencoder.". Autoencoders are composed of two parts: an encoder, which compresses an image into a small amount of data ...

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