activity
20222026
most citedHow to Boost Face Recognition with StyleGAN?

1 citations · 1 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2026

GHARP: Real-time Gaussian Head Animation from Large-scale Reconstruction Prior

Ali Benlalah, Sepehr Johari, Patricia Vitoria +14

We present GHARP (Real-time Gaussian Head Animation from Large-scale Reconstruction Prior), a method that animates 3D human heads in real time from a few input images of a subject…

cs.CV2026

Large-Scale High-Quality 3D Gaussian Head Reconstruction from Multi-View Captures

Evangelos Ntavelis, Sean Wu, Mohamad Shahbazi +21

We propose HeadsUp, a scalable feed-forward method for reconstructing high-quality 3D Gaussian heads from large-scale multi-camera setups. Our method employs an efficient encoder-d…

cs.CV2025

Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks

Dmitrii Pozdeev, Alexey Artemov, Ananta R. Bhattarai +1

We propose DenseMarks - a new learned representation for human heads, enabling high-quality dense correspondences of human head images. For a 2D image of a human head, a Vision Tra…

cs.GR2025

3DGH: 3D Head Generation with Composable Hair and Face

Chengan He, Junxuan Li, Tobias Kirschstein +7

We present 3DGH, an unconditional generative model for 3D human heads with composable hair and face components. Unlike previous work that entangles the modeling of hair and face, w…

cs.CV2025

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…

cs.CV2025

Avat3r: Large Animatable Gaussian Reconstruction Model for High-fidelity 3D Head Avatars

Tobias Kirschstein, Javier Romero, Artem Sevastopolsky +2

Traditionally, creating photo-realistic 3D head avatars requires a studio-level multi-view capture setup and expensive optimization during test-time, limiting the use of digital hu…

cs.CV2024

GaussianSpeech: Audio-Driven Gaussian Avatars

Shivangi Aneja, Artem Sevastopolsky, Tobias Kirschstein +3

We introduce GaussianSpeech, a novel approach that synthesizes high-fidelity animation sequences of photo-realistic, personalized 3D human head avatars from spoken audio. To captur…

cs.CV2023

HeadCraft: Modeling High-Detail Shape Variations for Animated 3DMMs

Artem Sevastopolsky, Philip-William Grassal, Simon Giebenhain +3

Current advances in human head modeling allow the generation of plausible-looking 3D head models via neural representations, such as NeRFs and SDFs. Nevertheless, constructing comp…

cs.CV2023

TriPlaneNet: An Encoder for EG3D Inversion

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…

cs.CV2022★ 1 cited

How to Boost Face Recognition with StyleGAN?

Artem Sevastopolsky, Yury Malkov, Nikita Durasov +2

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to cele…