755 citations · 4.3k across the 133 of their papers we have counts for
22 papers · 1 filter
Pixel Adaptive Filtering Units
Filippos Kokkinos, Ioannis Marras, Matteo Maggioni +2
State-of-the-art methods for computer vision rely heavily on the translation equivariance and spatial sharing properties of convolutional layers without explicitly taking into cons…
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator
Shunwang Gong, Lei Chen, Michael Bronstein +1
Intrinsic graph convolution operators with differentiable kernel functions play a crucial role in analyzing 3D shape meshes. In this paper, we present a fast and efficient intrinsi…
Extracting deep local features to detect manipulated images of human faces
Michail Tarasiou, Stefanos Zafeiriou
Recent developments in computer vision and machine learning have made it possible to create realistic manipulated videos of human faces, raising the issue of ensuring adequate prot…
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…
Complement Face Forensic Detection and Localization with FacialLandmarks
Kritaphat Songsri-in, Stefanos Zafeiriou
Recently, Generative Adversarial Networks (GANs) and image manipulating methods are becoming more powerful and can produce highly realistic face images beyond human recognition whi…
Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Automatic facial behavior analysis has a long history of studies in the intersection of computer vision, physiology and psychology. However it is only recently, with the collection…
Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset
Dimitrios Kollias, Stefanos Zafeiriou
This paper presents a novel CNN-RNN based approach, which exploits multiple CNN features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual-Emotion (…
Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace
Dimitrios Kollias, Stefanos Zafeiriou
Affective computing has been largely limited in terms of available data resources. The need to collect and annotate diverse in-the-wild datasets has become apparent with the rise o…
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…
SliderGAN: Synthesizing Expressive Face Images by Sliding 3D Blendshape Parameters
Evangelos Ververas, Stefanos Zafeiriou
Image-to-image (i2i) translation is the dense regression problem of learning how to transform an input image into an output using aligned image pairs. Remarkable progress has been…
PolyGAN: High-Order Polynomial Generators
Grigorios Chrysos, Stylianos Moschoglou, Yannis Panagakis +1
Generative Adversarial Networks (GANs) have become the gold standard when it comes to learning generative models for high-dimensional distributions. Since their advent, numerous va…
Video-to-Video Translation for Visual Speech Synthesis
Michail C. Doukas, Viktoriia Sharmanska, Stefanos Zafeiriou
Despite remarkable success in image-to-image translation that celebrates the advancements of generative adversarial networks (GANs), very limited attempts are known for video domai…
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…
RetinaFace: Single-stage Dense Face Localisation in the Wild
Jiankang Deng, Jia Guo, Yuxiang Zhou +3
Though tremendous strides have been made in uncontrolled face detection, accurate and efficient face localisation in the wild remains an open challenge. This paper presents a robus…
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…
Single Image 3D Hand Reconstruction with Mesh Convolutions
Dominik Kulon, Haoyang Wang, Riza Alp Güler +2
Monocular 3D reconstruction of deformable objects, such as human body parts, has been typically approached by predicting parameters of heavyweight linear models. In this paper, we…
Face Video Generation from a Single Image and Landmarks
Kritaphat Songsri-in, Stefanos Zafeiriou
In this paper we are concerned with the challenging problem of producing a full image sequence of a deformable face given only an image and generic facial motions encoded by a set…
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…
Dense 3D Face Decoding over 2500FPS: Joint Texture & Shape Convolutional Mesh Decoders
Yuxiang Zhou, Jiankang Deng, Irene Kotsia +1
3D Morphable Models (3DMMs) are statistical models that represent facial texture and shape variations using a set of linear bases and more particular Principal Component Analysis (…
MeshGAN: Non-linear 3D Morphable Models of Faces
Shiyang Cheng, Michael Bronstein, Yuxiang Zhou +3
Generative Adversarial Networks (GANs) are currently the method of choice for generating visual data. Certain GAN architectures and training methods have demonstrated exceptional p…
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…