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Related papers: Towards Native Generative Model for 3D Head Avatar

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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

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

3D modeling has long been an important area in computer vision and computer graphics. Recently, thanks to the breakthroughs in neural representations and generative models, we witnessed a rapid development of 3D modeling. 3D human modeling,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Ruihe Wang , Yukang Cao , Kai Han , Kwan-Yee K. Wong

While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing methods for learning generative models of 3D humans with diverse…

Computer Vision and Pattern Recognition · Computer Science 2023-05-04 Zijian Dong , Xu Chen , Jinlong Yang , Michael J. Black , Otmar Hilliges , Andreas Geiger

The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Alexander W. Bergman , Wang Yifan , Gordon Wetzstein

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

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

Unsupervised generation of clothed virtual humans with various appearance and animatable poses is important for creating 3D human avatars and other AR/VR applications. Existing methods are either limited to rigid object modeling, or not…

Computer Vision and Pattern Recognition · Computer Science 2022-08-02 Jianfeng Zhang , Zihang Jiang , Dingdong Yang , Hongyi Xu , Yichun Shi , Guoxian Song , Zhongcong Xu , Xinchao Wang , Jiashi Feng

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

Creating realistic avatars from a single RGB image is an attractive yet challenging problem. Due to its ill-posed nature, recent works leverage powerful prior from 2D diffusion models pretrained on large datasets. Although 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Yuxuan Xue , Xianghui Xie , Riccardo Marin , Gerard Pons-Moll

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries. Generally, two challenges remain in this field: i) existing methods struggle to generate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Xuanmeng Zhang , Jianfeng Zhang , Rohan Chacko , Hongyi Xu , Guoxian Song , Yi Yang , Jiashi Feng

Delivering immersive, 3D experiences for human communication requires a method to obtain 360 degree photo-realistic avatars of humans. To make these experiences accessible to all, only commodity hardware, like mobile phone cameras, should…

Computer Vision and Pattern Recognition · Computer Science 2022-10-24 Stanislaw Szymanowicz , Virginia Estellers , Tadas Baltrusaitis , Matthew Johnson

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability. This paper introduces a novel approach to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Zhixuan Yu , Ziqian Bai , Abhimitra Meka , Feitong Tan , Qiangeng Xu , Rohit Pandey , Sean Fanello , Hyun Soo Park , Yinda Zhang

Generative models aim to learn the distribution of observed data by generating new instances. With the advent of neural networks, deep generative models, including variational autoencoders (VAEs), generative adversarial networks (GANs), and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Zifan Shi , Sida Peng , Yinghao Xu , Andreas Geiger , Yiyi Liao , Yujun Shen

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

Creating realistic 3D objects and clothed avatars from a single RGB image is an attractive yet challenging problem. Due to its ill-posed nature, recent works leverage powerful prior from 2D diffusion models pretrained on large datasets.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yuxuan Xue , Xianghui Xie , Riccardo Marin , Gerard Pons-Moll

For humans, visual understanding is inherently generative: given a 3D shape, we can postulate how it would look in the world; given a 2D image, we can infer the 3D structure that likely gave rise to it. We can thus translate between the 2D…

Computer Vision and Pattern Recognition · Computer Science 2020-11-17 Tristan Aumentado-Armstrong , Alex Levinshtein , Stavros Tsogkas , Konstantinos G. Derpanis , Allan D. Jepson

To make 3D human avatars widely available, we must be able to generate a variety of 3D virtual humans with varied identities and shapes in arbitrary poses. This task is challenging due to the diversity of clothed body shapes, their complex…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Xu Chen , Tianjian Jiang , Jie Song , Jinlong Yang , Michael J. Black , Andreas Geiger , Otmar Hilliges

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

Generating animatable and editable 3D head avatars is essential for various applications in computer vision and graphics. Traditional 3D-aware generative adversarial networks (GANs), often using implicit fields like Neural Radiance Fields…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Guohao Li , Hongyu Yang , Yifang Men , Di Huang , Weixin Li , Ruijie Yang , Yunhong Wang
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