3 citations · 4 across the 3 of their papers we have counts for
7 papers
Efficient Hair Style Transfer with Generative Adversarial Networks
Muhammed Pektas, Baris Gecer, Aybars Ugur
Despite the recent success of image generation and style transfer with Generative Adversarial Networks (GANs), hair synthesis and style transfer remain challenging due to the shape…
3DMM-RF: Convolutional Radiance Fields for 3D Face Modeling
Stathis Galanakis, Baris Gecer, Alexandros Lattas +1
Facial 3D Morphable Models are a main computer vision subject with countless applications and have been highly optimized in the last two decades. The tremendous improvements of dee…
Facial Geometric Detail Recovery via Implicit Representation
Xingyu Ren, Alexandros Lattas, Baris Gecer +4
Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries thr…
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…
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…