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StyleGAN is a generative adversarial network (GAN) introduced by Nvidia researchers in December 2018, [1] and made source available in February 2019. [2][3] StyleGAN depends on Nvidia's CUDA software, GPUs, and Google's TensorFlow, [4] or Meta AI 's PyTorch, which supersedes TensorFlow as the official implementation library in later StyleGAN ...
Artbreeder. Artbreeder, formerly known as Ganbreeder, [4] is a collaborative, machine learning -based art website. Using the models StyleGAN and BigGAN, [4][5] the website allows users to generate and modify images of faces, landscapes, and paintings, among other categories. [6]
Artificial intelligence art is visual artwork created through the use of an artificial intelligence (AI) program. [ 1 ] Artists began to create artificial intelligence art in the mid to late 20th century, when the discipline was founded. Throughout its history, artificial intelligence art has raised many philosophical concerns related to the ...
Informally, eigenfaces can be considered a set of "standardized face ingredients", derived from statistical analysis of many pictures of faces. Any human face can be considered to be a combination of these standard faces. For example, one's face might be composed of the average face plus 10% from eigenface 1, 55% from eigenface 2, and even −3 ...
Human image synthesis is technology that can be applied to make believable and even photorealistic renditions [1] [2] of human-likenesses, moving or still. It has effectively existed since the early 2000s. Many films using computer generated imagery have featured synthetic images of human-like characters digitally composited onto the real or ...
FaceApp is a photo and video editing application for iOS and Android developed by FaceApp Technology Limited, a company based in Cyprus. [1] The app generates highly realistic transformations of human faces in photographs by using neural networks based on artificial intelligence. [2][3] The app can transform a face to make it smile, look ...
DALL·E, DALL·E 2, and DALL·E 3 (pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as "prompts". The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
The generator creates new images from the latent representation of the source material, while the discriminator attempts to determine whether or not the image is generated. [citation needed] This causes the generator to create images that mimic reality extremely well as any defects would be caught by the discriminator. [65]
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