Date: 12025-11-18

Type: quote

Tags: deepfake, ai, face manipulation

Source: https://facefusion.io/

Media: https://www.facefusion.co/_next/static/media/faceswap.153842a5.png

Deepfakes rely on a type of neural network called an autoencoder. These consist of an encoder, which reduces an image to a lower dimensional latent space, and a decoder, which reconstructs the image from the latent representation. Deepfakes utilize this architecture by having a universal encoder which encodes a person in to the latent space. The latent representation contains key features about their facial features and body posture. This can then be decoded with a model trained specifically for the target. This means the target's detailed information will be superimposed on the underlying facial and body features of the original video, represented in the latent space.