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Relightable 3D Head Portraits from a Smartphone Video
Artem Sevastopolsky, Savva Ignatiev, Gonzalo Ferrer +2
In this work, a system for creating a relightable 3D portrait of a human head is presented. Our neural pipeline operates on a sequence of frames captured by a smartphone camera wit…
Image Generators with Conditionally-Independent Pixel Synthesis
Ivan Anokhin, Kirill Demochkin, Taras Khakhulin +3
Existing image generator networks rely heavily on spatial convolutions and, optionally, self-attention blocks in order to gradually synthesize images in a coarse-to-fine manner. He…
TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer
Maria Kolos, Artem Sevastopolsky, Victor Lempitsky
We propose and evaluate a neural point-based graphics method that can model semi-transparent scene parts. Similarly to its predecessor pipeline, ours uses point clouds to model pro…
Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars
Egor Zakharov, Aleksei Ivakhnenko, Aliaksandra Shysheya +1
We propose a neural rendering-based system that creates head avatars from a single photograph. Our approach models a person's appearance by decomposing it into two layers. The firs…
DeepLandscape: Adversarial Modeling of Landscape Video
Elizaveta Logacheva, Roman Suvorov, Oleg Khomenko +2
We build a new model of landscape videos that can be trained on a mixture of static landscape images as well as landscape animations. Our architecture extends StyleGAN model by aug…
Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks
Kirill Mazur, Victor Lempitsky
We present a new versatile building block for deep point cloud processing architectures that is equally suited for diverse tasks. This building block combines the ideas of spatial…