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Related papers: HQ3DAvatar: High Quality Controllable 3D Head Avat…

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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 human doubles to the VFX industry or offline renderings. To…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Tobias Kirschstein , Javier Romero , Artem Sevastopolsky , Matthias Nießner , Shunsuke Saito

The ability to create realistic, animatable and relightable head avatars from casual video sequences would open up wide ranging applications in communication and entertainment. Current methods either build on explicit 3D morphable meshes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Yufeng Zheng , Wang Yifan , Gordon Wetzstein , Michael J. Black , Otmar Hilliges

Reconstructing animatable and high-quality 3D head avatars from monocular videos, especially with realistic relighting, is a valuable task. However, the limited information from single-view input, combined with the complex head poses and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Dongbin Zhang , Yunfei Liu , Lijian Lin , Ye Zhu , Kangjie Chen , Minghan Qin , Yu Li , Haoqian Wang

We present Neural Head Avatars, a novel neural representation that explicitly models the surface geometry and appearance of an animatable human avatar that can be used for teleconferencing in AR/VR or other applications in the movie or…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Philip-William Grassal , Malte Prinzler , Titus Leistner , Carsten Rother , Matthias Nießner , Justus Thies

Creating realistic 3D head assets for virtual characters that match a precise artistic vision remains labor-intensive. We present a novel framework that streamlines this process by providing artists with intuitive control over generated 3D…

There is a growing demand for the accessible creation of high-quality 3D avatars that are animatable and customizable. Although 3D morphable models provide intuitive control for editing and animation, and robustness for single-view face…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Connor Z. Lin , Koki Nagano , Jan Kautz , Eric R. Chan , Umar Iqbal , Leonidas Guibas , Gordon Wetzstein , Sameh Khamis

The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved. Existing 3D representations either perform well in the realism of portrait images synthesis or…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Xiaochen Zhao , Lizhen Wang , Jingxiang Sun , Hongwen Zhang , Jinli Suo , Yebin Liu

We introduce a novel approach to creating ultra-realistic head avatars and rendering them in real-time (>30fps at $2048 \times 1334$ resolution). First, we propose a hybrid explicit representation that combines the advantages of two…

Graphics · Computer Science 2025-02-20 Hongrui Cai , Yuting Xiao , Xuan Wang , Jiafei Li , Yudong Guo , Yanbo Fan , Shenghua Gao , Juyong Zhang

We introduce GaussianAvatars, a new method to create photorealistic head avatars that are fully controllable in terms of expression, pose, and viewpoint. The core idea is a dynamic 3D representation based on 3D Gaussian splats that are…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Shenhan Qian , Tobias Kirschstein , Liam Schoneveld , Davide Davoli , Simon Giebenhain , Matthias Nießner

We present an approach to generate high fidelity 3D face avatar with a high-resolution UV texture map from a single image. To estimate the face geometry, we use a deep neural network to directly predict vertex coordinates of the 3D face…

Computer Vision and Pattern Recognition · Computer Science 2019-12-10 Ruizhe Wang , Chih-Fan Chen , Hao Peng , Xudong Liu , Oliver Liu , Xin Li

Current text-to-avatar methods often rely on implicit representations (e.g., NeRF, SDF, and DMTet), leading to 3D content that artists cannot easily edit and animate in graphics software. This paper introduces a novel framework for…

Graphics · Computer Science 2025-05-01 Duotun Wang , Hengyu Meng , Zeyu Cai , Zhijing Shao , Qianxi Liu , Lin Wang , Mingming Fan , Xiaohang Zhan , Zeyu Wang

The human face is central to communication. For immersive applications, the digital presence of a person should mirror the physical reality, capturing the users idiosyncrasies and detailed facial expressions. However, current 3D head avatar…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Jalees Nehvi , Timo Bolkart , Thabo Beeler , Justus Thies

Creating high-fidelity 3D human head avatars is crucial for applications in VR/AR, digital human, and film production. Recent advances have leveraged morphable face models to generate animated head avatars from easily accessible data,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Yuelang Xu , Zhaoqi Su , Qingyao Wu , Yebin Liu

We introduce FlexAvatar, a method for creating high-quality and complete 3D head avatars from a single image. A core challenge lies in the limited availability of multi-view data and the tendency of monocular training to yield incomplete 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Tobias Kirschstein , Simon Giebenhain , Matthias Nießner

Sparse volumetric reconstruction and rendering via 3D Gaussian splatting have recently enabled animatable 3D head avatars that are rendered under arbitrary viewpoints with impressive photorealism. Today, such photoreal avatars are seen as a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Gengyan Li , Paulo Gotardo , Timo Bolkart , Stephan Garbin , Kripasindhu Sarkar , Abhimitra Meka , Alexandros Lattas , Thabo Beeler

Constructing vivid 3D head avatars for given subjects and realizing a series of animations on them is valuable yet challenging. This paper presents GaussianHead, which models the actional human head with anisotropic 3D Gaussians. In our…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Jie Wang , Jiu-Cheng Xie , Xianyan Li , Feng Xu , Chi-Man Pun , Hao Gao

Reconstructing personalized animatable head avatars has significant implications in the fields of AR/VR. Existing methods for achieving explicit face control of 3D Morphable Models (3DMM) typically rely on multi-view images or videos of a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Haoyu Ma , Tong Zhang , Shanlin Sun , Xiangyi Yan , Kun Han , Xiaohui Xie

Video-driven 3D facial animation transfer aims to drive avatars to reproduce the expressions of actors. Existing methods have achieved remarkable results by constraining both geometric and perceptual consistency. However, geometric…

Graphics · Computer Science 2024-10-10 Feng Qiu , Wei Zhang , Chen Liu , Rudong An , Lincheng Li , Yu Ding , Changjie Fan , Zhipeng Hu , Xin Yu

Recently, text-guided 3D generative methods have made remarkable advancements in producing high-quality textures and geometry, capitalizing on the proliferation of large vision-language and image diffusion models. However, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Xiao Han , Yukang Cao , Kai Han , Xiatian Zhu , Jiankang Deng , Yi-Zhe Song , Tao Xiang , Kwan-Yee K. Wong

High-quality reconstruction of controllable 3D head avatars from 2D videos is highly desirable for virtual human applications in movies, games, and telepresence. Neural implicit fields provide a powerful representation to model 3D head…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Chuhan Chen , Matthew O'Toole , Gaurav Bharaj , Pablo Garrido