Asset Type
ML Model
ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences
Provides a framework for learning text-driven generative paths in pre-trained GANs.
AI Assets related to #GANs
Asset Type
ML Model
WarpedGANSpace: Finding non-linear RBF paths in GAN latent space
Provides a framework for discovering non-linear interpretable paths in pre-trained GAN latent spaces.
Asset Type
ML Model
StyleMask: Disentangling the Style Space of StyleGAN2 for Neural Face Reenactment
Provides a Neural Face Reenactment framework by leveraging the expressiveness of the StyleGAN2’s style space.
Asset Type
ML Model
HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces
Provides a framework for the problem of Neural Face Reenactment using Generative Adversarial Networks (GANs).
Asset Type
ML Model
Tensor Component Analysis for Interpreting the Latent Space of GANs
Provides a framework for finding interpretable directions in the latent space of convolutional GANs.
Asset Type
Tutorial
Super Resolution Lecture
Nowadays, digital images and video are everywhere. Image Processing revolutionizes very many domains, notably: -Digital Media (video/image/movie) Content Production and Broadcasting, Social Media Analytics, -Medical/Biological/Dental Imaging and Diagn...
Education resources related to #GANs
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Recently, ChatGPT, along with DALL-E-2 and Codex ,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its impressive pe...
GANs for Media Content Generation
Generative Adversarial Networks (GANs) are part of the cutting edge in recent machine learning research. The lectures were presented live by senior or Postdoc researchers from several AI4Media consortium members and collaborators across Europe.
Generative Adversarial Networks in Multimedia Content Creation
Deep Convolutional Generative Adversarial Networks (DCGAN) have been used to generate highly compelling pictures or videos, such as manipulated facial animations, interior and outdoor images, videos.
Super Resolution Lecture
Nowadays, digital images and video are everywhere. Image Processing revolutionizes very many domains, notably: -Digital Media (video/image/movie) Content Production and Broadcasting, Social Media Analytics, -Medical/Biological/Dental Imaging and Diagn...