Victor Lempitsky

research

∙ 07/15/2022

MegaPortraits: One-shot Megapixel Neural Head Avatars

In this work, we advance the neural head avatar technology to the megapi...

Nikita Drobyshev, et al. ∙

research

∙ 06/16/2022

Realistic One-shot Mesh-based Head Avatars

We present a system for realistic one-shot mesh-based human head avatars...

Taras Khakhulin, et al. ∙

research

∙ 03/24/2022

NPBG++: Accelerating Neural Point-Based Graphics

We present a new system (NPBG++) for the novel view synthesis (NVS) task...

Ruslan Rakhimov, et al. ∙

research

∙ 01/13/2022

Stereo Magnification with Multi-Layer Images

Representing scenes with multiple semi-transparent colored layers has be...

Taras Khakhulin, et al. ∙

research

∙ 09/15/2021

Resolution-robust Large Mask Inpainting with Fourier Convolutions

Modern image inpainting systems, despite the significant progress, often...

Roman Suvorov, et al. ∙

research

∙ 05/05/2021

Perceptual Gradient Networks

Many applications of deep learning for image generation use perceptual l...

Dmitry Nikulin, et al. ∙

research

∙ 04/16/2021

StylePeople: A Generative Model of Fullbody Human Avatars

We propose a new type of full-body human avatars, which combines paramet...

Artur Grigorev, et al. ∙

research

∙ 04/16/2021

Point-Based Modeling of Human Clothing

We propose a new approach to human clothing modeling based on point clou...

Ilya Zakharkin, et al. ∙

research

∙ 03/05/2021

Real-time RGBD-based Extended Body Pose Estimation

We present a system for real-time RGBD-based estimation of 3D human pose...

Renat Bashirov, et al. ∙

research

∙ 01/27/2021

CNN with large memory layers

This work is centred around the recently proposed product key memory str...

Rasul Karimov, et al. ∙

research

∙ 12/17/2020

Relightable 3D Head Portraits from a Smartphone Video

In this work, a system for creating a relightable 3D portrait of a human...

Artem Sevastopolsky, et al. ∙

research

∙ 11/27/2020

Image Generators with Conditionally-Independent Pixel Synthesis

Existing image generator networks rely heavily on spatial convolutions a...

Ivan Anokhin, et al. ∙

research

∙ 09/06/2020

TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer

We propose and evaluate a neural point-based graphics method that can mo...

Maria Kolos, et al. ∙

research

∙ 08/24/2020

Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars

We propose a neural rendering-based system that creates head avatars fro...

Egor Zakharov, et al. ∙

research

∙ 08/21/2020

DeepLandscape: Adversarial Modeling of Landscape Video

We build a new model of landscape videos that can be trained on a mixtur...

Elizaveta Logacheva, et al. ∙

research

∙ 07/22/2020

Cloud Transformers

We present a new versatile building block for deep point cloud processin...

Kirill Mazur, et al. ∙

research

∙ 04/24/2020

Neural Head Reenactment with Latent Pose Descriptors

We propose a neural head reenactment system, which is driven by a latent...

Egor Burkov, et al. ∙

research

∙ 03/19/2020

High-Resolution Daytime Translation Without Domain Labels

Modeling daytime changes in high resolution photographs, e.g., re-render...

Ivan Anokhin, et al. ∙

research

∙ 06/29/2019

Stereo relative pose from line and point feature triplets

Stereo relative pose problem lies at the core of stereo visual odometry ...

Alexander Vakhitov, et al. ∙

research

∙ 06/19/2019

Neural Point-Based Graphics

We present a new point-based approach for modeling complex scenes. The a...

Kara-Ali Aliev, et al. ∙

research

∙ 05/21/2019

Textured Neural Avatars

We present a system for learning full-body neural avatars, i.e. deep net...

Aliaksandra Shysheya, et al. ∙

research

∙ 05/20/2019

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

Several recent works have shown how highly realistic human head images c...

Egor Zakharov, et al. ∙

research

∙ 05/14/2019

Learnable Triangulation of Human Pose

We present two novel solutions for multi-view 3D human pose estimation b...

Karim Iskakov, et al. ∙

research

∙ 04/10/2019

Instance Segmentation of Biological Images Using Harmonic Embeddings

We present a new instance segmentation approach tailored to biological i...

Victor Kulikov, et al. ∙

research

∙ 04/03/2019

Hyperbolic Image Embeddings

Computer vision tasks such as image classification, image retrieval and ...

Valentin Khrulkov, et al. ∙

research

∙ 11/28/2018

Coordinate-based Texture Inpainting for Pose-Guided Image Generation

We present a new deep learning approach to pose-guided resynthesis of hu...

Artur Grigorev, et al. ∙

research

∙ 09/05/2018

Image Manipulation with Perceptual Discriminators

Systems that perform image manipulation using deep convolutional network...

Diana Sungatullina, et al. ∙

research

∙ 07/26/2018

Instance Segmentation by Deep Coloring

We propose a new and, arguably, a very simple reduction of instance segm...

Victor Kulikov, et al. ∙

research

∙ 06/16/2018

Latent Convolutional Models

We present a new latent model of natural images that can be learned on l...

ShahRukh Athar, et al. ∙

research

∙ 06/13/2018

Impostor Networks for Fast Fine-Grained Recognition

In this work we introduce impostor networks, an architecture that allows...

Vadim Lebedev, et al. ∙

research

∙ 11/29/2017

Deep Image Prior

Deep convolutional networks have become a popular tool for image generat...

Dmitry Ulyanov, et al. ∙

research

∙ 10/17/2017

Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

We introduce a large-scale 3D shape understanding benchmark using data a...

Li Yi, et al. ∙

research

∙ 04/07/2017

It Takes (Only) Two: Adversarial Generator-Encoder Networks

We present a new autoencoder-type architecture that is trainable in an u...

Dmitry Ulyanov, et al. ∙

research

∙ 04/04/2017

Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models

We present a new deep learning architecture (called Kd-network) that is ...

Roman Klokov, et al. ∙

research

∙ 01/09/2017

Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis

The recent work of Gatys et al., who characterized the style of an image...

Dmitry Ulyanov, et al. ∙

research

∙ 12/19/2016

Parsing Images of Overlapping Organisms with Deep Singling-Out Networks

This work is motivated by the mostly unsolved task of parsing biological...

Victor Yurchenko, et al. ∙

research

∙ 11/17/2016

End-to-end Learning of Cost-Volume Aggregation for Real-time Dense Stereo

We present a new deep learning-based approach for dense stereo matching....

Andrey Kuzmin, et al. ∙

research

∙ 11/02/2016

Learning Deep Embeddings with Histogram Loss

We suggest a loss for learning deep embeddings. The new loss does not in...

Evgeniya Ustinova, et al. ∙

research

∙ 10/28/2016

Learnable Visual Markers

We propose a new approach to designing visual markers (analogous to QR-c...

Oleg Grinchuk, et al. ∙

research

∙ 07/27/2016

Instance Normalization: The Missing Ingredient for Fast Stylization

It this paper we revisit the fast stylization method introduced in Ulyan...

Dmitry Ulyanov, et al. ∙

research

∙ 07/25/2016

DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation

In this work, we consider the task of generating highly-realistic images...

Yaroslav Ganin, et al. ∙

research

∙ 06/05/2016

Pairwise Quantization

We consider the task of lossy compression of high-dimensional vectors th...

Artem Babenko, et al. ∙

research

∙ 03/10/2016

Texture Networks: Feed-forward Synthesis of Textures and Stylized Images

Gatys et al. recently demonstrated that deep networks can generate beaut...

Dmitry Ulyanov, et al. ∙

research

∙ 12/16/2015

Multiregion Bilinear Convolutional Neural Networks for Person Re-Identification

In this work we propose a new architecture for person re-identification....

Evgeniya Ustinova, et al. ∙

research

∙ 06/08/2015

Fast ConvNets Using Group-wise Brain Damage

We revisit the idea of brain damage, i.e. the pruning of the coefficient...

Vadim Lebedev, et al. ∙

research

∙ 05/28/2015

Domain-Adversarial Training of Neural Networks

We introduce a new representation learning approach for domain adaptatio...

Yaroslav Ganin, et al. ∙

research

∙ 12/19/2014

Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

We propose a simple two-step approach for speeding up convolution layers...

Vadim Lebedev, et al. ∙

research

∙ 09/26/2014

Unsupervised Domain Adaptation by Backpropagation

Top-performing deep architectures are trained on massive amounts of labe...

Yaroslav Ganin, et al. ∙

research

∙ 06/25/2014

N^4 -Fields: Neural Network Nearest Neighbor Fields for Image Transforms

We propose a new architecture for difficult image processing operations,...

Yaroslav Ganin, et al. ∙

Victor Lempitsky

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