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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

In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA). Our innovation lies in addressing the intricate challenges of delivering high-fidelity human body…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Xinqi Liu , Chenming Wu , Jialun Liu , Xing Liu , Jinbo Wu , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang

Reconstructing high-fidelity, animatable 3D head avatars from effortlessly captured monocular videos is a pivotal yet formidable challenge. Although significant progress has been made in rendering performance and manipulation capabilities,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Jiawei Zhang , Zijian Wu , Zhiyang Liang , Yicheng Gong , Dongfang Hu , Yao Yao , Xun Cao , Hao Zhu

The ability to animate photo-realistic head avatars reconstructed from monocular portrait video sequences represents a crucial step in bridging the gap between the virtual and real worlds. Recent advancements in head avatar techniques,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yufan Chen , Lizhen Wang , Qijing Li , Hongjiang Xiao , Shengping Zhang , Hongxun Yao , Yebin Liu

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

Reconstructing high-fidelity animatable human avatars from monocular videos remains challenging due to insufficient geometric information in single-view observations. While recent 3D Gaussian Splatting methods have shown promise, they…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Jinlong Fan , Bingyu Hu , Xingguang Li , Yuxiang Yang , Jing Zhang

Real-time rendering of human head avatars is a cornerstone of many computer graphics applications, such as augmented reality, video games, and films, to name a few. Recent approaches address this challenge with computationally efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Kartik Teotia , Hyeongwoo Kim , Pablo Garrido , Marc Habermann , Mohamed Elgharib , Christian Theobalt

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 propose a novel approach for reconstructing animatable 3D Gaussian avatars from monocular videos captured by commodity devices like smartphones. Photorealistic 3D head avatar reconstruction from such recordings is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Jiapeng Tang , Davide Davoli , Tobias Kirschstein , Liam Schoneveld , Matthias Niessner

Personalized 3D avatars require an animatable representation of digital humans. Doing so instantly from monocular videos offers scalability to broad class of users and wide-scale applications. In this paper, we present a fast, simple, yet…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Pramish Paudel , Anubhav Khanal , Ajad Chhatkuli , Danda Pani Paudel , Jyoti Tandukar

We introduce an approach that creates animatable human avatars from monocular videos using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields (NeRFs) achieve high-quality novel-view/novel-pose image synthesis but…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Zhiyin Qian , Shaofei Wang , Marko Mihajlovic , Andreas Geiger , Siyu Tang

Realistic digital avatars require expressive and dynamic hair motion; however, most existing head avatar methods assume rigid hair movement. These methods often fail to disentangle hair from the head, representing it as a simple outer shell…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Berna Kabadayi , Vanessa Sklyarova , Wojciech Zielonka , Justus Thies , Gerard Pons-Moll

Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision and graphics. While existing 3D human avatar modeling approaches can effectively capture…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Yuze Su , Hongsong Wang , Jie Gui , Liang Wang

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

We present HAHA - a novel approach for animatable human avatar generation from monocular input videos. The proposed method relies on learning the trade-off between the use of Gaussian splatting and a textured mesh for efficient and high…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 David Svitov , Pietro Morerio , Lourdes Agapito , Alessio Del Bue

Existing full-body Gaussian avatar methods primarily optimize global reconstruction quality and often fail to preserve fine-grained facial geometry and expression details. This challenge arises from limited facial representational capacity…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Willem Menu , Erkut Akdag , Pedro Quesado , Yasaman Kashefbahrami , Egor Bondarev

Despite recent progress in 3D Gaussian-based head avatar modeling, efficiently generating high fidelity avatars remains a challenge. Current methods typically rely on extensive multi-view capture setups or monocular videos with per-identity…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Xinya Ji , Sebastian Weiss , Manuel Kansy , Jacek Naruniec , Xun Cao , Barbara Solenthaler , Derek Bradley

High-quality, animatable 3D human avatar reconstruction from monocular videos offers significant potential for reducing reliance on complex hardware, making it highly practical for applications in game development, augmented reality, and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Xia Yuan , Hai Yuan , Wenyi Ge , Ying Fu , Xi Wu , Guanyu Xing

The creation of high-fidelity, digital versions of human heads is an important stepping stone in the process of further integrating virtual components into our everyday lives. Constructing such avatars is a challenging research problem, due…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Simon Giebenhain , Tobias Kirschstein , Martin Rünz , Lourdes Agapito , Matthias Nießner

Photorealistic and animatable human avatars are a key enabler for virtual/augmented reality, telepresence, and digital entertainment. While recent advances in 3D Gaussian Splatting (3DGS) have greatly improved rendering quality and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Cheng Peng , Jingxiang Sun , Yushuo Chen , Zhaoqi Su , Zhuo Su , Yebin Liu
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