papers

Publications (15)

cs.CV2022

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…

cs.CV2019

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…

cs.CV2018

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

Baris Gecer, Binod Bhattarai, Josef Kittler +1

We propose a novel end-to-end semi-supervised adversarial framework to generate photorealistic face images of new identities with wide ranges of expressions, poses, and illuminatio…

cs.CV2015

Evaluation of Joint Multi-Instance Multi-Label Learning For Breast Cancer Diagnosis

Baris Gecer, Ozge Yalcinkaya, Onur Tasar +1

Multi-instance multi-label (MIML) learning is a challenging problem in many aspects. Such learning approaches might be useful for many medical diagnosis applications including brea…

cs.CV2022

Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality

Amin Jourabloo, Baris Gecer, Fernando De la Torre +7

Social presence, the feeling of being there with a real person, will fuel the next generation of communication systems driven by digital humans in virtual reality (VR). The best 3D…

cs.CV2022

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2020

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…

cs.CV2020

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…

cs.CV2018

Learning Deep Convolutional Embeddings for Face Representation Using Joint Sample- and Set-based Supervision

Baris Gecer, Vassileios Balntas, Tae-Kyun Kim

In this work, we investigate several methods and strategies to learn deep embeddings for face recognition, using joint sample- and set-based optimization. We explain our framework…

cs.CV2022

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…

cs.CV2023

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…

cs.CV2020

OSTeC: One-Shot Texture Completion

Baris Gecer, Jiankang Deng, Stefanos Zafeiriou

The last few years have witnessed the great success of non-linear generative models in synthesizing high-quality photorealistic face images. Many recent 3D facial texture reconstru…

cs.CV2020

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…