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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

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

Building 3D animatable head avatars from a single image is an important yet challenging problem. Existing methods generally collapse under large camera pose variations, compromising the realism of 3D avatars. In this work, we propose a new…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Shuling Zhao , Dan Xu

We present a novel approach for generating animatable 3D-aware art avatars from a single image, with controllable facial expressions, head poses, and shoulder movements. Unlike previous reenactment methods, our approach utilizes a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Shaoxu Li

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

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

We present a new approach for video-driven animation of high-quality neural 3D head models, addressing the challenge of person-independent animation from video input. Typically, high-quality generative models are learned for specific…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Wolfgang Paier , Paul Hinzer , Anna Hilsmann , Peter Eisert

Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in AR or VR. Despite the progress, facial avatars reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Berna Kabadayi , Wojciech Zielonka , Bharat Lal Bhatnagar , Gerard Pons-Moll , Justus Thies

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

Head avatar reenactment focuses on creating animatable personal avatars from monocular videos, serving as a foundational element for applications like social signal understanding, gaming, human-machine interaction, and computer vision.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Wei Liang , Hui Yu , Derui Ding , Rachael E. Jack , Philippe G. Schyns

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

We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achieve user-controlled facial expressions and head poses. Our…

Reconstructing photorealistic and dynamic portrait avatars from images is essential to many applications including advertising, visual effects, and virtual reality. Depending on the application, avatar reconstruction involves different…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Felix Taubner , Ruihang Zhang , Mathieu Tuli , David B. Lindell

Faithful real-time facial animation is essential for avatar-mediated telepresence in Virtual Reality (VR). To emulate authentic communication, avatar animation needs to be efficient and accurate: able to capture both extreme and subtle…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Shaojie Bai , Te-Li Wang , Chenghui Li , Akshay Venkatesh , Tomas Simon , Chen Cao , Gabriel Schwartz , Ryan Wrench , Jason Saragih , Yaser Sheikh , Shih-En Wei

With the rapid advancement of 3D representation techniques and generative models, substantial progress has been made in reconstructing full-body 3D avatars from a single image. However, this task remains fundamentally ill-posedness due to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Gaofeng Liu , Hengsen Li , Ruoyu Gao , Xuetong Li , Zhiyuan Ma , Tao Fang

Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question of adding such controllability to text-to-3D generation. In…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Sungwon Hwang , Junha Hyung , Jaegul Choo

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

High-fidelity reconstruction of 3D human avatars has a wild application in visual reality. In this paper, we introduce FAGhead, a method that enables fully controllable human portraits from monocular videos. We explicit the traditional 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-01 Yixin Xuan , Xinyang Li , Gongxin Yao , Shiwei Zhou , Donghui Sun , Xiaoxin Chen , Yu Pan

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

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
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