no code implementations • 21 Dec 2023 • Artem Sevastopolsky, Philip-William Grassal, Simon Giebenhain, ShahRukh Athar, Luisa Verdoliva, Matthias Niessner
The decomposition of the parametric model and high-quality vertex displacements allows us to animate the model and modify it semantically.
no code implementations • 23 Mar 2023 • Ananta R. Bhattarai, Matthias Nießner, Artem Sevastopolsky
Recent progress in NeRF-based GANs has introduced a number of approaches for high-resolution and high-fidelity generative modeling of human heads with a possibility for novel view rendering.
1 code implementation • ICCV 2023 • Artem Sevastopolsky, Yury Malkov, Nikita Durasov, Luisa Verdoliva, Matthias Nießner
We show that a simple approach based on fine-tuning pSp encoder for StyleGAN allows us to improve upon the state-of-the-art facial recognition and performs better compared to training on synthetic face identities.
no code implementations • 17 Dec 2020 • Artem Sevastopolsky, Savva Ignatiev, Gonzalo Ferrer, Evgeny Burnaev, Victor Lempitsky
The model is fitted to the sequence of frames with human face-specific priors that enforce the plausibility of albedo-lighting decomposition and operates at the interactive frame rate.
1 code implementation • 6 Sep 2020 • Maria Kolos, Artem Sevastopolsky, Victor Lempitsky
New scenes can be modeled using gradient-based optimization of neural descriptors and of the rendering network.
7 code implementations • ECCV 2020 • Kara-Ali Aliev, Artem Sevastopolsky, Maria Kolos, Dmitry Ulyanov, Victor Lempitsky
A deep rendering network is learned in parallel with the descriptors, so that new views of the scene can be obtained by passing the rasterizations of a point cloud from new viewpoints through this network.
1 code implementation • 28 Nov 2018 • Artur Grigorev, Artem Sevastopolsky, Alexander Vakhitov, Victor Lempitsky
Since the input photograph always observes only a part of the surface, we suggest a new inpainting method that completes the texture of the human body.
no code implementations • 30 Apr 2018 • Artem Sevastopolsky, Stepan Drapak, Konstantin Kiselev, Blake M. Snyder, Jeremy D. Keenan, Anastasia Georgievskaya
In this work, we propose a special cascade network for image segmentation, which is based on the U-Net networks as building blocks and the idea of the iterative refinement.
2 code implementations • 4 Apr 2017 • Artem Sevastopolsky
If undiagnosed in time, glaucoma causes irreversible damage to the optic nerve leading to blindness.