Face generation is the task of generating (or interpolating) new faces from an existing dataset.
The state-of-the-art results for this task are located in the Image Generation parent.
( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )
The free access to large-scale public databases, together with the fast progress of deep learning techniques, in particular Generative Adversarial Networks, have led to the generation of very realistic fake content with its corresponding implications towards society in this era of fake news.
We describe a new training methodology for generative adversarial networks.
Ranked #1 on
Image Generation
on CelebA-HQ 256x256
In this paper, we are interested in generating fine-grained cartoon faces for various groups.
Recent advances in Generative Adversarial Networks (GANs) have shown impressive results for task of facial expression synthesis.
CONDITIONAL IMAGE GENERATION FACE GENERATION IMAGE-TO-IMAGE TRANSLATION
In this paper, we present the Surrey Face Model, a multi-resolution 3D Morphable Model that we make available to the public for non-commercial purposes.
3D FACE RECONSTRUCTION FACE GENERATION FACE MODEL FACE RECOGNITION FACIAL LANDMARK DETECTION HEAD POSE ESTIMATION
We present a generic image-to-image translation framework, Pixel2Style2Pixel (pSp).
CONDITIONAL IMAGE GENERATION FACE GENERATION IMAGE-TO-IMAGE TRANSLATION
In this work, we propose a framework called InterFaceGAN to interpret the disentangled face representation learned by the state-of-the-art GAN models and study the properties of the facial semantics encoded in the latent space.
In this work, we propose a novel framework, called InterFaceGAN, for semantic face editing by interpreting the latent semantics learned by GANs.
Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech.
Our technique employs expression analysis for proxy face geometry generation and combines supervised and unsupervised learning for facial detail synthesis.