303 citations · 529 across the 14 of their papers we have counts for
18 papers · 1 filter
GNM Head: A Generative aNthropometric Model of the human head
Stylianos Ploumpis, Jan Bednarik, Gaspard Zoss +29
Parametric models of the human head are essential tools traditionally used in computer vision and graphics for animation, rendering, and reconstruction. More recently, they serve a…
ShapeFusion: A 3D diffusion model for localized shape editing
Rolandos Alexandros Potamias, Michail Tarasiou, Stylianos Ploumpis +1
In the realm of 3D computer vision, parametric models have emerged as a ground-breaking methodology for the creation of realistic and expressive 3D avatars. Traditionally, they rel…
AnimateMe: 4D Facial Expressions via Diffusion Models
Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias +4
The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent…
Locally Adaptive Neural 3D Morphable Models
Michail Tarasiou, Rolandos Alexandros Potamias, Eimear O'Sullivan +2
We present the Locally Adaptive Morphable Model (LAMM), a highly flexible Auto-Encoder (AE) framework for learning to generate and manipulate 3D meshes. We train our architecture f…
FitMe: Deep Photorealistic 3D Morphable Model Avatars
Alexandros Lattas, Stylianos Moschoglou, Stylianos Ploumpis +3
In this paper, we introduce FitMe, a facial reflectance model and a differentiable rendering optimization pipeline, that can be used to acquire high-fidelity renderable human avata…
Dynamic Neural Portraits
Michail Christos Doukas, Stylianos Ploumpis, Stefanos Zafeiriou
We present Dynamic Neural Portraits, a novel approach to the problem of full-head reenactment. Our method generates photo-realistic video portraits by explicitly controlling head p…
AvatarMe++: Facial Shape and BRDF Inference with Photorealistic Rendering-Aware GANs
Alexandros Lattas, Stylianos Moschoglou, Stylianos Ploumpis +3
Over the last years, many face analysis tasks have accomplished astounding performance, with applications including face generation and 3D face reconstruction from a single "in-the…
3D human tongue reconstruction from single "in-the-wild" images
Stylianos Ploumpis, Stylianos Moschoglou, Vasileios Triantafyllou +1
3D face reconstruction from a single image is a task that has garnered increased interest in the Computer Vision community, especially due to its broad use in a number of applicati…
Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction
Baris Gecer, Stylianos Ploumpis, Irene Kotsia +1
A lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In the rec…
Learning to Generate Customized Dynamic 3D Facial Expressions
Rolandos Alexandros Potamias, Jiali Zheng, Stylianos Ploumpis +3
Recent advances in deep learning have significantly pushed the state-of-the-art in photorealistic video animation given a single image. In this paper, we extrapolate those advances…
AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
Alexandros Lattas, Stylianos Moschoglou, Baris Gecer +4
Over the last years, with the advent of Generative Adversarial Networks (GANs), many face analysis tasks have accomplished astounding performance, with applications including, but…
Towards a complete 3D morphable model of the human head
Stylianos Ploumpis, Evangelos Ververas, Eimear O' Sullivan +6
Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of…
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…
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation
Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis +2
Generative models for 3D geometric data arise in many important applications in 3D computer vision and graphics. In this paper, we focus on 3D deformable shapes that share a common…
Combining 3D Morphable Models: A Large scale Face-and-Head Model
Stylianos Ploumpis, Haoyang Wang, Nick Pears +2
Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D surfaces of an object class. In this context, we identify an interesting question…
GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
Baris Gecer, Stylianos Ploumpis, Irene Kotsia +1
In the past few years, a lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Netwo…
3D Face Morphable Models "In-the-Wild"
James Booth, Epameinondas Antonakos, Stylianos Ploumpis +3
3D Morphable Models (3DMMs) are powerful statistical models of 3D facial shape and texture, and among the state-of-the-art methods for reconstructing facial shape from single image…