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The manipulation of latent space has recently become an interesting topic in the field of generative models. Recent research shows that latent directions can be used to manipulate images towards certain attributes. However, controlling the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Zehranaz Canfes , M. Furkan Atasoy , Alara Dirik , Pinar Yanardag

Stylized 3D avatars have become increasingly prominent in our modern life. Creating these avatars manually usually involves laborious selection and adjustment of continuous and discrete parameters and is time-consuming for average users.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-16 Shen Sang , Tiancheng Zhi , Guoxian Song , Minghao Liu , Chunpong Lai , Jing Liu , Xiang Wen , James Davis , Linjie Luo

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

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…

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

Real-time, streaming interactive avatars represent a critical yet challenging goal in digital human research. Although diffusion-based human avatar generation methods achieve remarkable success, their non-causal architecture and high…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Zhiyao Sun , Ziqiao Peng , Yifeng Ma , Yi Chen , Zhengguang Zhou , Zixiang Zhou , Guozhen Zhang , Youliang Zhang , Yuan Zhou , Qinglin Lu , Yong-Jin Liu

We introduce a highly robust GAN-based framework for digitizing a normalized 3D avatar of a person from a single unconstrained photo. While the input image can be of a smiling person or taken in extreme lighting conditions, our method can…

Computer Vision and Pattern Recognition · Computer Science 2021-06-23 Huiwen Luo , Koki Nagano , Han-Wei Kung , Mclean Goldwhite , Qingguo Xu , Zejian Wang , Lingyu Wei , Liwen Hu , Hao Li

Text-to-image (T2I) generation has achieved remarkable progress in instruction following and aesthetics. However, a persistent challenge is the prevalence of physical artifacts, such as anatomical and structural flaws, which severely…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Jia Wang , Jie Hu , Xiaoqi Ma , Hanghang Ma , Yanbing Zeng , Xiaoming Wei

Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of truly interactive communication, often generating one-way…

Machine Learning · Computer Science 2026-01-05 Taekyung Ki , Sangwon Jang , Jaehyeong Jo , Jaehong Yoon , Sung Ju Hwang

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

In this paper, we rethink text-to-avatar generative models by proposing TeRA, a more efficient and effective framework than the previous SDS-based models and general large 3D generative models. Our approach employs a two-stage training…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Yanwen Wang , Yiyu Zhuang , Jiawei Zhang , Li Wang , Yifei Zeng , Xun Cao , Xinxin Zuo , Hao Zhu

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

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

The creation of a parameterized stylized character involves careful selection of numerous parameters, also known as the "avatar vectors" that can be interpreted by the avatar engine. Existing unsupervised avatar vector estimation methods…

Computer Vision and Pattern Recognition · Computer Science 2023-02-20 Shizun Wang , Weihong Zeng , Xu Wang , Hao Yang , Li Chen , Yi Yuan , Yunzhao Zeng , Min Zheng , Chuang Zhang , Ming Wu

Conversation is an essential component of virtual avatar activities in the metaverse. With the development of natural language processing, textual and vocal conversation generation has achieved a significant breakthrough. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Yichao Yan , Zanwei Zhou , Zi Wang , Jingnan Gao , Xiaokang Yang

High-fidelity digital human representations are increasingly in demand in the digital world, particularly for interactive telepresence, AR/VR, 3D graphics, and the rapidly evolving metaverse. Even though they work well in small spaces,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Zexu Huang , Sarah Monazam Erfani , Siying Lu , Mingming Gong

Generating high-fidelity upper-body 3D avatars from one-shot input image remains a significant challenge. Current 3D avatar generation methods, which rely on large reconstruction models, are fast and capable of producing stable body…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Fan Yang , Heyuan Li , Peihao Li , Weihao Yuan , Lingteng Qiu , Chaoyue Song , Cheng Chen , Yisheng He , Shifeng Zhang , Xiaoguang Han , Steven Hoi , Guosheng Lin

Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional methods for avatar creation often involve time-consuming…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Keqiang Sun , Amin Jourabloo , Riddhish Bhalodia , Moustafa Meshry , Yu Rong , Zhengyu Yang , Thu Nguyen-Phuoc , Christian Haene , Jiu Xu , Sam Johnson , Hongsheng Li , Sofien Bouaziz

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors. In the first stage, we optimize a neural radiance field to produce…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Guocheng Qian , Jinjie Mai , Abdullah Hamdi , Jian Ren , Aliaksandr Siarohin , Bing Li , Hsin-Ying Lee , Ivan Skorokhodov , Peter Wonka , Sergey Tulyakov , Bernard Ghanem

High-fidelity reconstruction of head avatars from monocular videos is highly desirable for virtual human applications, but it remains a challenge in the fields of computer graphics and computer vision. In this paper, we propose a two-phase…

Graphics · Computer Science 2025-03-31 Pilseo Park , Ze Zhang , Michel Sarkis , Ning Bi , Xiaoming Liu , Yiying Tong