50 citations · 73 across the 20 of their papers we have counts for
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GeoRelight: Learning Joint Geometrical Relighting and Reconstruction with Flexible Multi-Modal Diffusion Transformers
Yuxuan Xue, Ruofan Liang, Egor Zakharov +6
Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and illumination. Current method…
GenLCA: 3D Diffusion for Full-Body Avatars from In-the-Wild Videos
Yiqian Wu, Rawal Khirodkar, Egor Zakharov +6
We present GenLCA, a diffusion-based generative model for generating and editing photorealistic full-body avatars from text and image inputs. The generated avatars are faithful to…
Large-scale Codec Avatars: The Unreasonable Effectiveness of Large-scale Avatar Pretraining
Junxuan Li, Rawal Khirodkar, Chengan He +37
High-quality 3D avatar modeling faces a critical trade-off between fidelity and generalization. On the one hand, multi-view studio data enables high-fidelity modeling of humans wit…
CamLit: Unified Video Diffusion with Explicit Camera and Lighting Control
Zhiyi Kuang, Chengan He, Egor Zakharov +6
We present CamLit, the first unified video diffusion model that jointly performs novel view synthesis (NVS) and relighting from a single input image. Given one reference image, a u…
FactorPortrait: Controllable Portrait Animation via Disentangled Expression, Pose, and Viewpoint
Jiapeng Tang, Kai Li, Chengxiang Yin +8
We introduce FactorPortrait, a video diffusion method for controllable portrait animation that enables lifelike synthesis from disentangled control signals of facial expressions, h…
Im2Haircut: Single-view Strand-based Hair Reconstruction for Human Avatars
Vanessa Sklyarova, Egor Zakharov, Malte Prinzler +3
We present a novel approach for 3D hair reconstruction from single photographs based on a global hair prior combined with local optimization. Capturing strand-based hair geometry f…
GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans
Rachmadio Noval Lazuardi, Artem Sevastopolsky, Egor Zakharov +2
We propose a novel method that reconstructs hair strands directly from colorless 3D scans by leveraging multi-modal hair orientation extraction. Hair strand reconstruction is a fun…
Joker: Conditional 3D Head Synthesis with Extreme Facial Expressions
Malte Prinzler, Egor Zakharov, Vanessa Sklyarova +2
We introduce Joker, a new method for the conditional synthesis of 3D human heads with extreme expressions. Given a single reference image of a person, we synthesize a volumetric hu…
Human Hair Reconstruction with Strand-Aligned 3D Gaussians
Egor Zakharov, Vanessa Sklyarova, Michael Black +3
We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions fr…
VOODOO XP: Expressive One-Shot Head Reenactment for VR Telepresence
Phong Tran, Egor Zakharov, Long-Nhat Ho +7
We introduce VOODOO XP: a 3D-aware one-shot head reenactment method that can generate highly expressive facial expressions from any input driver video and a single 2D portrait. Our…
HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles
Vanessa Sklyarova, Egor Zakharov, Otmar Hilliges +2
We present HAAR, a new strand-based generative model for 3D human hairstyles. Specifically, based on textual inputs, HAAR produces 3D hairstyles that could be used as production-le…
VOODOO 3D: Volumetric Portrait Disentanglement for One-Shot 3D Head Reenactment
Phong Tran, Egor Zakharov, Long-Nhat Ho +3
We present a 3D-aware one-shot head reenactment method based on a fully volumetric neural disentanglement framework for source appearance and driver expressions. Our method is real…
Neural Haircut: Prior-Guided Strand-Based Hair Reconstruction
Vanessa Sklyarova, Jenya Chelishev, Andreea Dogaru +3
Generating realistic human 3D reconstructions using image or video data is essential for various communication and entertainment applications. While existing methods achieved impre…
Sphere-Guided Training of Neural Implicit Surfaces
Andreea Dogaru, Andrei Timotei Ardelean, Savva Ignatyev +2
In recent years, neural distance functions trained via volumetric ray marching have been widely adopted for multi-view 3D reconstruction. These methods, however, apply the ray marc…
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…
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…
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…
Textured Neural Avatars
Aliaksandra Shysheya, Egor Zakharov, Kara-Ali Aliev +9
We present a system for learning full-body neural avatars, i.e. deep networks that produce full-body renderings of a person for varying body pose and camera position. Our system ta…
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Egor Zakharov, Aliaksandra Shysheya, Egor Burkov +1
Several recent works have shown how highly realistic human head images can be obtained by training convolutional neural networks to generate them. In order to create a personalized…
Image Manipulation with Perceptual Discriminators
Diana Sungatullina, Egor Zakharov, Dmitry Ulyanov +1
Systems that perform image manipulation using deep convolutional networks have achieved remarkable realism. Perceptual losses and losses based on adversarial discriminators are the…