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3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

We introduce TADA, a simple-yet-effective approach that takes textual descriptions and produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be animated and rendered with traditional graphics pipelines.…

Artificial Intelligence · Computer Science 2023-08-22 Tingting Liao , Hongwei Yi , Yuliang Xiu , Jiaxaing Tang , Yangyi Huang , Justus Thies , Michael J. Black

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

Current text-to-avatar methods often rely on implicit representations (e.g., NeRF, SDF, and DMTet), leading to 3D content that artists cannot easily edit and animate in graphics software. This paper introduces a novel framework for…

Graphics · Computer Science 2025-05-01 Duotun Wang , Hengyu Meng , Zeyu Cai , Zhijing Shao , Qianxi Liu , Lin Wang , Mingming Fan , Xiaohang Zhan , Zeyu Wang

Recently, 2D speaking avatars have increasingly participated in everyday scenarios due to the fast development of facial animation techniques. However, most existing works neglect the explicit control of human bodies. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jiazhi Guan , Quanwei Yang , Kaisiyuan Wang , Hang Zhou , Shengyi He , Zhiliang Xu , Haocheng Feng , Errui Ding , Jingdong Wang , Hongtao Xie , Youjian Zhao , Ziwei Liu

Powered by large-scale text-to-image generation models, text-to-3D avatar generation has made promising progress. However, most methods fail to produce photorealistic results, limited by imprecise geometry and low-quality appearance.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yuanyou Xu , Zongxin Yang , Yi Yang

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

Generating 3D human models directly from text helps reduce the cost and time of character modeling. However, achieving multi-attribute controllable and realistic 3D human avatar generation is still challenging due to feature coupling and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Chaoqun Gong , Yuqin Dai , Ronghui Li , Achun Bao , Jun Li , Jian Yang , Yachao Zhang , Xiu Li

We introduce SimAvatar, a framework designed to generate simulation-ready clothed 3D human avatars from a text prompt. Current text-driven human avatar generation methods either model hair, clothing, and the human body using a unified…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Xueting Li , Ye Yuan , Shalini De Mello , Gilles Daviet , Jonathan Leaf , Miles Macklin , Jan Kautz , Umar Iqbal

Leveraging pretrained 2D diffusion models and score distillation sampling (SDS), recent methods have shown promising results for text-to-3D avatar generation. However, generating high-quality 3D avatars capable of expressive animation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Yukun Huang , Jianan Wang , Ailing Zeng , Zheng-Jun Zha , Lei Zhang , Xihui Liu

Diffusion models trained on large-scale text-image datasets have demonstrated a strong capability of controllable high-quality image generation from arbitrary text prompts. However, the generation quality and generalization ability of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Ying-Tian Liu , Yuan-Chen Guo , Guan Luo , Heyi Sun , Wei Yin , Song-Hai Zhang

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

While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a significant challenge due to the complexities of multi-view consistency and spatial control.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jinxin Ai , Matthias Nießner , Ziya Erkoç

Estimating 3D articulated shapes like animal bodies from monocular images is inherently challenging due to the ambiguities of camera viewpoint, pose, texture, lighting, etc. We propose ARTIC3D, a self-supervised framework to reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2023-06-08 Chun-Han Yao , Amit Raj , Wei-Chih Hung , Yuanzhen Li , Michael Rubinstein , Ming-Hsuan Yang , Varun Jampani

To integrate digital humans into everyday life, there is a strong demand for generating high-quality, fine-grained disentangled 3D avatars that support expressive animation and simulation capabilities, ideally from low-cost textual inputs.…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Xiaokun Sun , Zhenyu Zhang , Ying Tai , Hao Tang , Zili Yi , Jian Yang

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D approaches often grapple with challenges such as…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yiwen Chen , Chi Zhang , Xiaofeng Yang , Zhongang Cai , Gang Yu , Lei Yang , Guosheng Lin

Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the back view) and inaccurate shapes (e.g., animals with extra…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Cheng Chen , Xiaofeng Yang , Fan Yang , Chengzeng Feng , Zhoujie Fu , Chuan-Sheng Foo , Guosheng Lin , Fayao Liu

While recent works have achieved great success on image-to-3D object generation, high quality and fidelity 3D head generation from a single image remains a great challenge. Previous text-based methods for generating 3D heads were limited by…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Jinkun Hao , Junshu Tang , Jiangning Zhang , Ran Yi , Yijia Hong , Moran Li , Weijian Cao , Yating Wang , Chengjie Wang , Lizhuang Ma

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Generating 3D faces from textual descriptions has a multitude of applications, such as gaming, movie, and robotics. Recent progresses have demonstrated the success of unconditional 3D face generation and text-to-3D shape generation.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Cuican Yu , Guansong Lu , Yihan Zeng , Jian Sun , Xiaodan Liang , Huibin Li , Zongben Xu , Songcen Xu , Wei Zhang , Hang Xu