Facial Expression Translation
3 papers with code • 3 benchmarks • 2 datasets
CelebA
MH-FED
Latest papers
Facial Expression Translation using Landmark Guided GANs
We propose a simple yet powerful Landmark guided Generative Adversarial Network (LandmarkGAN) for the facial expression-to-expression translation using a single image, which is an important and challenging task in computer vision since the expression-to-expression translation is a non-linear and non-aligned problem.
Toward Fine-grained Facial Expression Manipulation
junleen/Expression-manipulator
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ECCV 2020
Previous methods edit an input image under the guidance of a discrete emotion label or absolute condition (e. g., facial action units) to possess the desired expression.
Unified Generative Adversarial Networks for Controllable Image-to-Image Translation
The proposed model consists of a single generator and a discriminator taking a conditional image and the target controllable structure as input.
