388 citations · 461 across the 4 of their papers we have counts for
5 papers
Latent Disentanglement in Mesh Variational Autoencoders Improves the Diagnosis of Craniofacial Syndromes and Aids Surgical Planning
Simone Foti, Alexander J. Rickart, Bongjin Koo +9
The use of deep learning to undertake shape analysis of the complexities of the human head holds great promise. However, there have traditionally been a number of barriers to accur…
Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks
Baris Gecer, Alexander Lattas, Stylianos Ploumpis +4
Generating realistic 3D faces is of high importance for computer graphics and computer vision applications. Generally, research on 3D face generation revolves around linear statist…
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation
Stylianos Moschoglou, Stylianos Ploumpis, Mihalis Nicolaou +2
Over the past few years, Generative Adversarial Networks (GANs) have garnered increased interest among researchers in Computer Vision, with applications including, but not limited…
Synthesising 3D Facial Motion from "In-the-Wild" Speech
Panagiotis Tzirakis, Athanasios Papaioannou, Alexander Lattas +3
Synthesising 3D facial motion from speech is a crucial problem manifesting in a multitude of applications such as computer games and movies. Recently proposed methods tackle this p…
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
Dimitrios Kollias, Panagiotis Tzirakis, Mihalis A. Nicolaou +5
Automatic understanding of human affect using visual signals is of great importance in everyday human-machine interactions. Appraising human emotional states, behaviors and reactio…