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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

Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications. However, existing methods often struggle to model challenging facial…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Cong Wang , Di Kang , Yan-Pei Cao , Linchao Bao , Ying Shan , Song-Hai Zhang

Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynamic performances is to track the underlying geometry using a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Kartik Teotia , Mallikarjun B R , Xingang Pan , Hyeongwoo Kim , Pablo Garrido , Mohamed Elgharib , Christian Theobalt

To bring digital avatars into people's lives, it is highly demanded to efficiently generate complete, realistic, and animatable head avatars. This task is challenging, and it is difficult for existing methods to satisfy all the requirements…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Sijing Wu , Yichao Yan , Yunhao Li , Yuhao Cheng , Wenhan Zhu , Ke Gao , Xiaobo Li , Guangtao Zhai

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

Computationally weak systems and demanding graphical applications are still mostly dependent on linear blendshapes for facial animations. The accompanying artifacts such as self-intersections, loss of volume, or missing soft tissue…

Graphics · Computer Science 2023-01-23 Nicolas Wagner , Ulrich Schwanecke , Mario Botsch

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

3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability. We present a novel representation that enables…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Safa C. Medin , Gengyan Li , Ruofei Du , Stephan Garbin , Philip Davidson , Gregory W. Wornell , Thabo Beeler , Abhimitra Meka

In this paper, we propose HeadNeRF, a novel NeRF-based parametric head model that integrates the neural radiance field to the parametric representation of the human head. It can render high fidelity head images in real-time on modern GPUs,…

Computer Vision and Pattern Recognition · Computer Science 2022-05-03 Yang Hong , Bo Peng , Haiyao Xiao , Ligang Liu , Juyong Zhang

Recently, implicit neural representation has been widely used to generate animatable human avatars. However, the materials and geometry of those representations are coupled in the neural network and hard to edit, which hinders their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Qifeng Chen , Rengan Xie , Kai Huang , Qi Wang , Wenting Zheng , Rong Li , Yuchi Huo

Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details. Neural volumetric representations approach photorealism but are hard to animate and do not…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Yufeng Zheng , Victoria Fernández Abrevaya , Marcel C. Bühler , Xu Chen , Michael J. Black , Otmar Hilliges

We introduce 3D Gaussian blendshapes for modeling photorealistic head avatars. Taking a monocular video as input, we learn a base head model of neutral expression, along with a group of expression blendshapes, each of which corresponds to a…

Graphics · Computer Science 2024-05-03 Shengjie Ma , Yanlin Weng , Tianjia Shao , Kun Zhou

We present Dynamic Neural Portraits, a novel approach to the problem of full-head reenactment. Our method generates photo-realistic video portraits by explicitly controlling head pose, facial expressions and eye gaze. Our proposed…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Michail Christos Doukas , Stylianos Ploumpis , Stefanos Zafeiriou

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

Over the last years, 3D morphable models (3DMMs) have emerged as a state-of-the-art methodology for modeling and generating expressive 3D avatars. However, given their reliance on a strict topology, along with their linear nature, they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Rolandos Alexandros Potamias , Stathis Galanakis , Jiankang Deng , Athanasios Papaioannou , Stefanos Zafeiriou

We propose a novel neural architecture for representing 3D surfaces, which harnesses two complementary shape representations: (i) an explicit representation via an atlas, i.e., embeddings of 2D domains into 3D; (ii) an implicit-function…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Omid Poursaeed , Matthew Fisher , Noam Aigerman , Vladimir G. Kim

Our goal is to efficiently learn personalized animatable 3D head avatars from videos that are geometrically accurate, realistic, relightable, and compatible with current rendering systems. While 3D meshes enable efficient processing and are…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Shrisha Bharadwaj , Yufeng Zheng , Otmar Hilliges , Michael J. Black , Victoria Fernandez-Abrevaya

We propose FlashAvatar, a novel and lightweight 3D animatable avatar representation that could reconstruct a digital avatar from a short monocular video sequence in minutes and render high-fidelity photo-realistic images at 300FPS on a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jun Xiang , Xuan Gao , Yudong Guo , Juyong Zhang

We present PrismAvatar: a 3D head avatar model which is designed specifically to enable real-time animation and rendering on resource-constrained edge devices, while still enjoying the benefits of neural volumetric rendering at training…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Prashant Raina , Felix Taubner , Mathieu Tuli , Eu Wern Teh , Kevin Ferreira

Building photorealistic, animatable full-body digital humans remains a longstanding challenge in computer graphics and vision. Recent advances in animatable avatar modeling have largely progressed along two directions: improving the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Heming Zhu , Guoxing Sun , Marc Habermann
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