Egor Zakharov

I am a Postdoc at ETH Zurich AIT lab. My research interests include computer vision and graphics for the problems of 3D reconstruction and image animation.

I received my Ph.D. from Skoltech, under the supervision of Victor Lempitsky. During my Ph.D., I also was a Lead Research Scientist at Samsung AI Center.

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Representative papers are highlighted.

VOODOO 3D: Volumetric Portrait Disentanglement for One-Shot 3D Head Reenactment
Phong Tran, Egor Zakharov Long Nhat Ho, Anh Tuan Tran, Liwen Hu, Hao Li
CVPR, 2024
project page / video / arXiv

Synthesis of animatable and view-consistent human head avatars from a single image.

HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles
Vanessa Sklyarova, Egor Zakharov Otmar Hilliges, Michael J. Black, Justus Thies
CVPR, 2024
project page / video / arXiv

Text-guided generation and editing of strand-based hairstyles.

Neural Haircut: Prior-Guided Strand-Based Hair Reconstruction
Vanessa Sklyarova, Jenya Chelishev, Igor Medvedev, Andreea Dogaru, Victor Lempitsky, Egor Zakharov
ICCV, 2023   (Oral Presentation)   top 1.8% of the submissions
project page / video / arXiv

Reconstructing personalized and realistic hairstyles in the form of 3D strands from a smartphone video.

Sphere-Guided Training of Neural Implicit Surfaces
Andreea Dogaru, Andrei-Timotei Ardelean, Savva Ignatyev, Egor Zakharov, Evgeny Burnaev
CVPR, 2023
project page / arXiv

We improve existing surface reconstruction methods using a plug-and-play hybrid representation, achieving up-to 18% improvement in reconstruction quality and approx. 2x faster convergence speed.

Realistic One-shot Mesh-based Head Avatars
Taras Khakhulin, Vanessa Sklyarova, Victor Lempitsky, Egor Zakharov
ECCV, 2022
project page / arXiv

We create animatable 3D head reconstructions in the form of a rigged mesh from a single image by leveraging facial priors and differentiable rendering of in-the-wild video data.

MegaPortraits: One-shot Megapixel Neural Head Avatars
Nikita Drobyshev, Jenya Chelishev, Taras Khakhulin, Aleksei Ivakhnenko, Victor Lempitsky, Egor Zakharov
ACM MM, 2022
project page / arXiv

Learning disentangled expression and appearance representations for high-resolution portrait animation.

Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars
Egor Zakharov, Aleksei Ivakhnenko, Aliaksandra Shysheya, Victor Lempitsky
ECCV, 2020
project page / video / arXiv

Speeding-up the inference of neural head avatars using an efficient architecture that achieves real-time performance on mobile.

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Egor Zakharov, Aliaksandra Shysheya, Egor Burkov, Victor Lempitsky
ICCV, 2019   (Oral Presentation)   top 4.6% of the submissions
video / arXiv

Leveraging a large corpus of weakly annotated video data to achieve the realistic synthesis of human heads in a few-shot scenario using meta-learning and GAN-based training.

Textured Neural Avatars
Aliaksandra Shysheya, Egor Zakharov, Kara-Ali Aliev, Renat Bashirov, Egor Burkov, Karim Iskakov, Aleksei Ivakhnenko, Yury Malkov, Igor Pasechnik, Dmitry Ulyanov, Alexander Vakhitov, Victor Lempitsky
CVPR, 2019   (Oral Presentation)   top 5.6% of the submissions
project page / arXiv

We integrated classical and neural rendering approaches to achieve high robustness of the avatar renders to the poses and views unseen during training.

Image Manipulation with Perceptual Discriminators
Diana Sungatullina, Egor Zakharov, Dmitry Ulyanov, Victor Lempitsky
ECCV, 2018
project page / arXiv

We combine the GAN-based and perceptual losses in a single training method, which primarily excels at the task of facial attribute manipulation.

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