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This paper presents a 3D generative model that uses diffusion models to automatically generate 3D digital avatars represented as neural radiance fields. A significant challenge in generating such avatars is that the memory and processing…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Tengfei Wang , Bo Zhang , Ting Zhang , Shuyang Gu , Jianmin Bao , Tadas Baltrusaitis , Jingjing Shen , Dong Chen , Fang Wen , Qifeng Chen , Baining Guo

We present AvatarPopUp, a method for fast, high quality 3D human avatar generation from different input modalities, such as images and text prompts and with control over the generated pose and shape. The common theme is the use of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Nikos Kolotouros , Thiemo Alldieck , Enric Corona , Eduard Gabriel Bazavan , Cristian Sminchisescu

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

Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Haoran Wei , Wencheng Han , Xingping Dong , Jianbing Shen

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

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

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

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

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

We introduce AvatarBooth, a novel method for generating high-quality 3D avatars using text prompts or specific images. Unlike previous approaches that can only synthesize avatars based on simple text descriptions, our method enables the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-19 Yifei Zeng , Yuanxun Lu , Xinya Ji , Yao Yao , Hao Zhu , Xun Cao

The recent advancements in image-text diffusion models have stimulated research interest in large-scale 3D generative models. Nevertheless, the limited availability of diverse 3D resources presents significant challenges to learning. In…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Chi Zhang , Yiwen Chen , Yijun Fu , Zhenglin Zhou , Gang YU , Billzb Wang , Bin Fu , Tao Chen , Guosheng Lin , Chunhua Shen

In this work, we introduce a novel high-fidelity 3D head reconstruction method from a single portrait image, regardless of perspective, expression, or accessories. Despite significant efforts in adapting 2D generative models for novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Jianfu Zhang , Yujie Gao , Jiahui Zhan , Wentao Wang , Yiyi Zhang , Haohua Zhao , Liqing Zhang

With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in 4D generative modeling, existing methods exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Eddie Pokming Sheung , Qihao Liu , Wufei Ma , Prakhar Kaushik , Jianwen Xie , Alan Yuille

We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by recent methods on text-guided 3D common object generation,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Reconstructing photorealistic and animatable 4D head avatars from a single portrait image remains a fundamental challenge in computer vision. While diffusion models have enabled remarkable progress in image and video generation for avatar…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Chao Xu , Xiaochen Zhao , Xiang Deng , Jingxiang Sun , Donglin Di , Zhuo Su , Yebin Liu

Creating human avatars is a highly desirable yet challenging task. Recent advancements in radiance field rendering have achieved unprecedented photorealism and real-time performance for personalized dynamic human avatars. However, these…

Graphics · Computer Science 2025-09-09 Dongliang Cao , Guoxing Sun , Marc Habermann , Florian Bernard

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

Recent advances in 3D avatar generation have gained significant attentions. These breakthroughs aim to produce more realistic animatable avatars, narrowing the gap between virtual and real-world experiences. Most of existing works employ…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Mingyuan Zhou , Rakib Hyder , Ziwei Xuan , Guojun Qi

This work focuses on open-domain 4D avatarization, with the purpose of creating a 4D avatar from a portrait image in an arbitrary style. We select parametric triplanes as the intermediate 4D representation and propose a practical training…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Hongyu Liu , Xuan Wang , Ziyu Wan , Yue Ma , Jingye Chen , Yanbo Fan , Yujun Shen , Yibing Song , Qifeng Chen

Diffusion models have shown impressive potential on talking head generation. While plausible appearance and talking effect are achieved, these methods still suffer from temporal, 3D or expression inconsistency due to the error accumulation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang
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