activity
20192023
most citedHumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion

142 citations · 228 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2023★ 142 cited

HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion

Mustafa Işık, Martin Rünz, Markos Georgopoulos +4

Representing human performance at high-fidelity is an essential building block in diverse applications, such as film production, computer games or videoconferencing. To close the g…

cs.CV2022

Self-improving Multiplane-to-layer Images for Novel View Synthesis

Pavel Solovev, Taras Khakhulin, Denis Korzhenkov

We present a new method for lightweight novel-view synthesis that generalizes to an arbitrary forward-facing scene. Recent approaches are computationally expensive, require per-sce…

cs.CV2022

MegaPortraits: One-shot Megapixel Neural Head Avatars

Nikita Drobyshev, Jenya Chelishev, Taras Khakhulin +3

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 th…

cs.CV2022

Realistic One-shot Mesh-based Head Avatars

Taras Khakhulin, Vanessa Sklyarova, Victor Lempitsky +1

We present a system for realistic one-shot mesh-based human head avatars creation, ROME for short. Using a single photograph, our model estimates a person-specific head mesh and th…

cs.CV2022

Stereo Magnification with Multi-Layer Images

Taras Khakhulin, Denis Korzhenkov, Pavel Solovev +3

Representing scenes with multiple semi-transparent colored layers has been a popular and successful choice for real-time novel view synthesis. Existing approaches infer colors and…

cs.CV2020

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…

quant-ph2020★ 19 cited

Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation

Roman Schutski, Dmitry Kolmakov, Taras Khakhulin +1

Tensor networks are the main building blocks in a wide variety of computational sciences, ranging from many-body theory and quantum computing to probability and machine learning. H…

cs.CV2020★ 67 cited

High-Resolution Daytime Translation Without Domain Labels

Ivan Anokhin, Pavel Solovev, Denis Korzhenkov +6

Modeling daytime changes in high resolution photographs, e.g., re-rendering the same scene under different illuminations typical for day, night, or dawn, is a challenging image man…

cs.LG2019

Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics

Taras Khakhulin, Roman Schutski, Ivan Oseledets

We propose a Reinforcement Learning based approach to approximately solve the Tree Decomposition (TD) problem. TD is a combinatorial problem, which is central to the analysis of gr…