no code implementations • CVPR 2023 • Polina Karpikova, Radionova Ekaterina, Anastasia Yaschenko, Andrei Spiridonov, Leonid Kostyushko, Riccardo Fabbricatore, Aleksei Ivakhnenko
Generative DNNs are a powerful tool for image synthesis, but they are limited by their computational load.
no code implementations • 15 Jul 2022 • Nikita Drobyshev, Jenya Chelishev, Taras Khakhulin, Aleksei Ivakhnenko, Victor Lempitsky, Egor Zakharov
In this work, we advance the neural head avatar technology to the megapixel resolution while focusing on the particularly challenging task of cross-driving synthesis, i. e., when the appearance of the driving image is substantially different from the animated source image.
1 code implementation • 5 May 2021 • Dmitry Nikulin, Roman Suvorov, Aleksei Ivakhnenko, Victor Lempitsky
The use of perceptual loss however incurs repeated forward-backward passes in a large image classification network as well as a considerable memory overhead required to store the activations of this network.
1 code implementation • ECCV 2020 • Egor Zakharov, Aleksei Ivakhnenko, Aliaksandra Shysheya, Victor Lempitsky
The texture image is generated offline, warped and added to the coarse image to ensure a high effective resolution of synthesized head views.
no code implementations • CVPR 2019 • 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
In particular, our system estimates an explicit two-dimensional texture map of the model surface.