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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

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

In this paper, we introduce GaussianMotion, a novel human rendering model that generates fully animatable scenes aligned with textual descriptions using Gaussian Splatting. Although existing methods achieve reasonable text-to-3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Gyumin Shim , Sangmin Lee , Jaegul Choo

The introduction of 3D Gaussian blendshapes has enabled the real-time reconstruction of animatable head avatars from monocular video. Toonify, a StyleGAN-based method, has become widely used for facial image stylization. To extend Toonify…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Rui-Yang Ju , Sheng-Yen Huang , Yi-Ping Hung

We present GaussianAvatar, an efficient approach to creating realistic human avatars with dynamic 3D appearances from a single video. We start by introducing animatable 3D Gaussians to explicitly represent humans in various poses and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Liangxiao Hu , Hongwen Zhang , Yuxiang Zhang , Boyao Zhou , Boning Liu , Shengping Zhang , Liqiang Nie

With the booming of virtual reality (VR) technology, there is a growing need for customized 3D avatars. However, traditional methods for 3D avatar modeling are either time-consuming or fail to retain similarity to the person being modeled.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Chuanyu Pan , Guowei Yang , Taijiang Mu , Yu-Kun Lai

Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos, and most methods lack precise control over gestures and expressions. To push this boundary, we address the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jun Xiang , Yudong Guo , Leipeng Hu , Boyang Guo , Yancheng Yuan , Juyong Zhang

Significant progress has been made for speech-driven 3D face animation, but most works focus on learning the motion of mesh/geometry, ignoring the impact of dynamic texture. In this work, we reveal that dynamic texture plays a key role in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Xuanchen Li , Jianyu Wang , Yuhao Cheng , Yikun Zeng , Xingyu Ren , Wenhan Zhu , Weiming Zhao , Yichao Yan

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

Real-time rendering of high-fidelity and animatable avatars from monocular videos remains a challenging problem in computer vision and graphics. Over the past few years, the Neural Radiance Field (NeRF) has made significant progress in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Qipeng Yan , Mingyang Sun , Lihua Zhang

Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising. One significant unresolved aspect within T2V is the effective visualization of text within generated videos. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Lin Liu , Quande Liu , Shengju Qian , Yuan Zhou , Wengang Zhou , Houqiang Li , Lingxi Xie , Qi Tian

Recent large-scale text-to-image generation models have made significant improvements in the quality, realism, and diversity of the synthesized images and enable users to control the created content through language. However, the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Samaneh Azadi , Thomas Hayes , Akbar Shah , Guan Pang , Devi Parikh , Sonal Gupta

We study the problem of creating high-fidelity and animatable 3D avatars from only textual descriptions. Existing text-to-avatar methods are either limited to static avatars which cannot be animated or struggle to generate animatable…

Graphics · Computer Science 2023-11-30 Jianfeng Zhang , Xuanmeng Zhang , Huichao Zhang , Jun Hao Liew , Chenxu Zhang , Yi Yang , Jiashi Feng

Due to the increasing demand in films and games, synthesizing 3D avatar animation has attracted much attention recently. In this work, we present a production-ready text/speech-driven full-body animation synthesis system. Given the text and…

Graphics · Computer Science 2022-06-01 Wenlin Zhuang , Jinwei Qi , Peng Zhang , Bang Zhang , Ping Tan

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

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 are interested in a novel task, namely low-resource text-to-talking avatar. Given only a few-minute-long talking person video with the audio track as the training data and arbitrary texts as the driving input, we aim to synthesize…

Computer Vision and Pattern Recognition · Computer Science 2023-08-03 Zhenhui Ye , Ziyue Jiang , Yi Ren , Jinglin Liu , Chen Zhang , Xiang Yin , Zejun Ma , Zhou Zhao

We present EmbodiedHead, a speech-driven talking-head framework that equips LLMs with real-time visual avatars for conversation. A practical embodied avatar must achieve real-time generation, unified listening-speaking behavior, and high…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Yu Zhang , Kaiyuan Shen , Yang Li

Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question of adding such controllability to text-to-3D generation. In…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Sungwon Hwang , Junha Hyung , Jaegul Choo

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