Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Ververas, Evangelos"'
Autor:
Ververas, Evangelos, Potamias, Rolandos Alexandros, Song, Jifei, Deng, Jiankang, Zafeiriou, Stefanos
Following the advent of NeRFs, 3D Gaussian Splatting (3D-GS) has paved the way to real-time neural rendering overcoming the computational burden of volumetric methods. Following the pioneering work of 3D-GS, several methods have attempted to achieve
Externí odkaz:
http://arxiv.org/abs/2404.19149
Autor:
Baltatzis, Vasileios, Potamias, Rolandos Alexandros, Ververas, Evangelos, Sun, Guanxiong, Deng, Jiankang, Zafeiriou, Stefanos
Sign Languages (SL) serve as the primary mode of communication for the Deaf and Hard of Hearing communities. Deep learning methods for SL recognition and translation have achieved promising results. However, Sign Language Production (SLP) poses a cha
Externí odkaz:
http://arxiv.org/abs/2312.02702
Autor:
Ververas, Evangelos, Gkagkos, Polydefkis, Deng, Jiankang, Doukas, Michail Christos, Guo, Jia, Zafeiriou, Stefanos
Developing gaze estimation models that generalize well to unseen domains and in-the-wild conditions remains a challenge with no known best solution. This is mostly due to the difficulty of acquiring ground truth data that cover the distribution of fa
Externí odkaz:
http://arxiv.org/abs/2212.02997
We present Free-HeadGAN, a person-generic neural talking head synthesis system. We show that modeling faces with sparse 3D facial landmarks are sufficient for achieving state-of-the-art generative performance, without relying on strong statistical pr
Externí odkaz:
http://arxiv.org/abs/2208.02210
Autor:
Potamias, Rolandos Alexandros, Zheng, Jiali, Ploumpis, Stylianos, Bouritsas, Giorgos, Ververas, Evangelos, Zafeiriou, Stefanos
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 to the 3D domain, by studying 3D image-to-video translation with a pa
Externí odkaz:
http://arxiv.org/abs/2007.09805
Autor:
Ploumpis, Stylianos, Ververas, Evangelos, Sullivan, Eimear O', Moschoglou, Stylianos, Wang, Haoyang, Pears, Nick, Smith, William A. P., Gecer, Baris, Zafeiriou, Stefanos
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 the human head to date that includes face, cranium, ears, eyes, teeth
Externí odkaz:
http://arxiv.org/abs/1911.08008
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 made in i2i translation with the advent of Deep Convolutional Neural N
Externí odkaz:
http://arxiv.org/abs/1908.09638
This paper presents a novel approach for synthesizing facial affect; either in terms of the six basic expressions (i.e., anger, disgust, fear, joy, sadness and surprise), or in terms of valence (i.e., how positive or negative is an emotion) and arous
Externí odkaz:
http://arxiv.org/abs/1811.05027
Autor:
Moschoglou, Stylianos, Ververas, Evangelos, Panagakis, Yannis, Nicolaou, Mihalis, Zafeiriou, Stefanos
Recently, due to the collection of large scale 3D face models, as well as the advent of deep learning, a significant progress has been made in the field of 3D face alignment "in-the-wild". That is, many methods have been proposed that establish spars
Externí odkaz:
http://arxiv.org/abs/1712.05799
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