Search Results for author: Baris Gecer

Found 12 papers, 9 papers with code

Facial Geometric Detail Recovery via Implicit Representation

1 code implementation18 Mar 2022 Xingyu Ren, Alexandros Lattas, Baris Gecer, Jiankang Deng, Chao Ma, Xiaokang Yang, Stefanos Zafeiriou

Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed.

AvatarMe++: Facial Shape and BRDF Inference with Photorealistic Rendering-Aware GANs

1 code implementation11 Dec 2021 Alexandros Lattas, Stylianos Moschoglou, Stylianos Ploumpis, Baris Gecer, Abhijeet Ghosh, Stefanos Zafeiriou

Nevertheless, to the best of our knowledge, there is no method which can produce render-ready high-resolution 3D faces from "in-the-wild" images and this can be attributed to the: (a) scarcity of available data for training, and (b) lack of robust methodologies that can successfully be applied on very high-resolution data.

3D Face Reconstruction Face Generation

Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction

1 code implementation16 May 2021 Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou

In this paper, we take a radically different approach and harness the power of Generative Adversarial Networks (GANs) and DCNNs in order to reconstruct the facial texture and shape from single images.

3D Face Reconstruction

Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality

no code implementations CVPR 2022 Amin Jourabloo, Baris Gecer, Fernando de la Torre, Jason Saragih, Shih-En Wei, Te-Li Wang, Stephen Lombardi, Danielle Belko, Autumn Trimble, Hernan Badino

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).

OSTeC: One-Shot Texture Completion

1 code implementation CVPR 2021 Baris Gecer, Jiankang Deng, Stefanos Zafeiriou

Many recent 3D facial texture reconstruction and pose manipulation from a single image approaches still rely on large and clean face datasets to train image-to-image Generative Adversarial Networks (GANs).

Face Recognition Robust Face Recognition

AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"

1 code implementation CVPR 2020 Alexandros Lattas, Stylianos Moschoglou, Baris Gecer, Stylianos Ploumpis, Vasileios Triantafyllou, Abhijeet Ghosh, Stefanos Zafeiriou

Over the last years, with the advent of Generative Adversarial Networks (GANs), many face analysis tasks have accomplished astounding performance, with applications including, but not limited to, face generation and 3D face reconstruction from a single "in-the-wild" image.

3D Face Reconstruction Face Generation

Towards a complete 3D morphable model of the human head

1 code implementation18 Nov 2019 Stylianos Ploumpis, Evangelos Ververas, Eimear O' Sullivan, Stylianos Moschoglou, Haoyang Wang, Nick Pears, William A. P. Smith, Baris Gecer, Stefanos Zafeiriou

Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity.

Face Model

GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction

1 code implementation CVPR 2019 Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou

In this paper, we take a radically different approach and harness the power of Generative Adversarial Networks (GANs) and DCNNs in order to reconstruct the facial texture and shape from single images.

 Ranked #1 on 3D Face Reconstruction on Florence (Average 3D Error metric)

3D Face Reconstruction

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

1 code implementation ECCV 2018 Baris Gecer, Binod Bhattarai, Josef Kittler, Tae-Kyun Kim

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 illuminations conditioned by a 3D morphable model.

Domain Adaptation Face Generation +3

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

no code implementations1 Aug 2017 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.

Face Recognition

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