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It is extremely challenging to create an animatable clothed human avatar from RGB videos, especially for loose clothes due to the difficulties in motion modeling. To address this problem, we introduce a novel representation on the basis of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zerong Zheng , Han Huang , Tao Yu , Hongwen Zhang , Yandong Guo , Yebin Liu

In this paper, we propose a novel hybrid representation and end-to-end trainable network architecture to model fully editable and customizable neural avatars. At the core of our work lies a representation that combines the modeling power of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Hsuan-I Ho , Lixin Xue , Jie Song , Otmar Hilliges

While generative models such as text-to-image, large language models and text-to-video have seen significant progress, the extension to text-to-virtual-reality remains largely unexplored, due to a deficit in training data and the complexity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Vriksha Srihari , R. Bhavya , Shruti Jayaraman , V. Mary Anita Rajam

Modeling animatable human avatars from monocular or multi-view videos has been widely studied, with recent approaches leveraging neural radiance fields (NeRFs) or 3D Gaussian Splatting (3DGS) achieving impressive results in novel-view and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yahui Li , Zhi Zeng , Liming Pang , Guixuan Zhang , Shuwu Zhang

The rise of 3D anime-style avatars in gaming, virtual reality, and other digital media has driven significant interest in automated generation methods capable of capturing their distinctive visual characteristics. These include stylized…

Graphics · Computer Science 2026-03-31 Fernanda Miyuki Yamada , João Paulo Gois , Hiroki Takahashi

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

Diffusion-based models have gained wide adoption in the virtual human generation due to their outstanding expressiveness. However, their substantial computational requirements have constrained their deployment in real-time interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Haojie Yu , Zhaonian Wang , Yihan Pan , Meng Cheng , Hao Yang , Chao Wang , Tao Xie , Xiaoming Xu , Xiaoming Wei , Xunliang Cai

The rising demand for creating lifelike avatars in the digital realm has led to an increased need for generating high-quality human videos guided by textual descriptions and poses. We propose Dancing Avatar, designed to fabricate human…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Bosheng Qin , Wentao Ye , Qifan Yu , Siliang Tang , Yueting Zhuang

We present InstructHumans, a novel framework for instruction-driven {animatable} 3D human texture editing. Existing text-based 3D editing methods often directly apply Score Distillation Sampling (SDS). SDS, designed for generation tasks,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Jiayin Zhu , Linlin Yang , Angela Yao

To adequately utilize the available image evidence in multi-view video-based avatar modeling, we propose TexVocab, a novel avatar representation that constructs a texture vocabulary and associates body poses with texture maps for animation.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Yuxiao Liu , Zhe Li , Yebin Liu , Haoqian Wang

We introduce GaussianSpeech, a novel approach that synthesizes high-fidelity animation sequences of photo-realistic, personalized 3D human head avatars from spoken audio. To capture the expressive, detailed nature of human heads, including…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Shivangi Aneja , Artem Sevastopolsky , Tobias Kirschstein , Justus Thies , Angela Dai , Matthias Nießner

Constructing drivable and photorealistic 3D head avatars has become a central task in AR/XR, enabling immersive and expressive user experiences. With the emergence of high-fidelity and efficient representations such as 3D Gaussians, recent…

Graphics · Computer Science 2025-12-25 Jaeseong Lee , Junyeong Ahn , Taewoong Kang , Jaegul Choo

Reconstructing photo-realistic drivable human avatars from multi-view image sequences has been a popular and challenging topic in the field of computer vision and graphics. While existing NeRF-based methods can achieve high-quality novel…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yujiao Jiang , Qingmin Liao , Xiaoyu Li , Li Ma , Qi Zhang , Chaopeng Zhang , Zongqing Lu , Ying Shan

Animating stylized avatars with dynamic poses and expressions has attracted increasing attention for its broad range of applications. Previous research has made significant progress by training controllable generative models to synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Ken Chen , Sachith Seneviratne , Wei Wang , Dongting Hu , Sanjay Saha , Md. Tarek Hasan , Sanka Rasnayaka , Tamasha Malepathirana , Mingming Gong , Saman Halgamuge

Realistic digital avatars require expressive and dynamic hair motion; however, most existing head avatar methods assume rigid hair movement. These methods often fail to disentangle hair from the head, representing it as a simple outer shell…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Berna Kabadayi , Vanessa Sklyarova , Wojciech Zielonka , Justus Thies , Gerard Pons-Moll

We present a new approach for video-driven animation of high-quality neural 3D head models, addressing the challenge of person-independent animation from video input. Typically, high-quality generative models are learned for specific…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Wolfgang Paier , Paul Hinzer , Anna Hilsmann , Peter Eisert

We present a system for learning full-body neural avatars, i.e. deep networks that produce full-body renderings of a person for varying body pose and camera position. Our system takes the middle path between the classical graphics pipeline…

Creating high-fidelity, animatable 3D talking heads is crucial for immersive applications, yet often hindered by the prevalence of low-quality image or video sources, which yield poor 3D reconstructions. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Ding-Jiun Huang , Yuanhao Wang , Shao-Ji Yuan , Albert Mosella-Montoro , Francisco Vicente Carrasco , Cheng Zhang , Fernando De la Torre

In contrast to the traditional avatar creation pipeline which is a costly process, contemporary generative approaches directly learn the data distribution from photographs. While plenty of works extend unconditional generative models and…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Junshu Tang , Bo Zhang , Binxin Yang , Ting Zhang , Dong Chen , Lizhuang Ma , Fang Wen

Visual storytelling with diffusion models has made impressive strides in maintaining character consistency across narrative scenes. However, a critical gap remains: while these methods ensure a character remains consistent across scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Manogna Sreenivas , Rohit Kumar , Soma Biswas