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Related papers: ZeroAvatar: Zero-shot 3D Avatar Generation from a …

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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

We present an approach to generate a 360-degree view of a person with a consistent, high-resolution appearance from a single input image. NeRF and its variants typically require videos or images from different viewpoints. Most existing…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Badour AlBahar , Shunsuke Saito , Hung-Yu Tseng , Changil Kim , Johannes Kopf , Jia-Bin Huang

Generating high-fidelity 3D avatars from text or image prompts is highly sought after in virtual reality and human-computer interaction. However, existing text-driven methods often rely on iterative Score Distillation Sampling (SDS) or CLIP…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Hong Li , Yutang Feng , Minqi Meng , Yichen Yang , Xuhui Liu , Baochang Zhang

We propose a method for synthesizing edited photo-realistic digital avatars with text instructions. Given a short monocular RGB video and text instructions, our method uses an image-conditioned diffusion model to edit one head image and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Shaoxu Li

We present DreamHuman, a method to generate realistic animatable 3D human avatar models solely from textual descriptions. Recent text-to-3D methods have made considerable strides in generation, but are still lacking in important aspects.…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Nikos Kolotouros , Thiemo Alldieck , Andrei Zanfir , Eduard Gabriel Bazavan , Mihai Fieraru , Cristian Sminchisescu

We present an approach to generate high fidelity 3D face avatar with a high-resolution UV texture map from a single image. To estimate the face geometry, we use a deep neural network to directly predict vertex coordinates of the 3D face…

Computer Vision and Pattern Recognition · Computer Science 2019-12-10 Ruizhe Wang , Chih-Fan Chen , Hao Peng , Xudong Liu , Oliver Liu , Xin Li

Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xiyi Chen , Marko Mihajlovic , Shaofei Wang , Sergey Prokudin , Siyu Tang

Animation techniques bring digital 3D worlds and characters to life. However, manual animation is tedious and automated techniques are often specialized to narrow shape classes. In our work, we propose a technique for automatic re-animation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Lukas Uzolas , Elmar Eisemann , Petr Kellnhofer

The generation of high-quality, animatable 3D head avatars from text has enormous potential in content creation applications such as games, movies, and embodied virtual assistants. Current text-to-3D generation methods typically combine…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Yiqian Wu , Malte Prinzler , Xiaogang Jin , Siyu Tang

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

The success of image generative models has enabled us to build methods that can edit images based on text or other user input. However, these methods are bespoke, imprecise, require additional information, or are limited to only 2D image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Rahul Sajnani , Jeroen Vanbaar , Jie Min , Kapil Katyal , Srinath Sridhar

We propose PFAvatar (Pose-Fusion Avatar), a new method that reconstructs high-quality 3D avatars from Outfit of the Day(OOTD) photos, which exhibit diverse poses, occlusions, and complex backgrounds. Our method consists of two stages: (1)…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Dianbing Xi , Guoyuan An , Jingsen Zhu , Zhijian Liu , Yuan Liu , Ruiyuan Zhang , Jiayuan Lu , Yuchi Huo , Rui Wang

We introduce TurboPortrait3D: a method for low-latency novel-view synthesis of human portraits. Our approach builds on the observation that existing image-to-3D models for portrait generation, while capable of producing renderable 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Emily Kim , Julieta Martinez , Timur Bagautdinov , Jessica Hodgins

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

DiffusionAvatars synthesizes a high-fidelity 3D head avatar of a person, offering intuitive control over both pose and expression. We propose a diffusion-based neural renderer that leverages generic 2D priors to produce compelling images of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Tobias Kirschstein , Simon Giebenhain , Matthias Nießner

Existing methods for image-to-3D avatar generation struggle to produce highly detailed, animation-ready avatars suitable for real-world applications. We introduce AdaHuman, a novel framework that generates high-fidelity animatable 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Yangyi Huang , Ye Yuan , Xueting Li , Jan Kautz , Umar Iqbal

Two major approaches exist for creating animatable human avatars. The first, a 3D-based approach, optimizes a NeRF- or 3DGS-based avatar from videos of a single person, achieving personalization through a disentangled identity…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Geonhee Sim , Gyeongsik Moon

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

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

We propose a method for synthesizing photo-realistic digital avatars from only one portrait as the reference. Given a portrait, our method synthesizes a coarse talking head video using driving keypoints features. And with the coarse video,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Shaoxu Li