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Text-driven avatar generation has gained significant attention owing to its convenience. However, existing methods typically model the human body with all garments as a single 3D model, limiting its usability, such as clothing replacement,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Jingyu Zhuang , Di Kang , Linchao Bao , Liang Lin , Guanbin Li

Avatar modelling has broad applications in human animation and virtual try-ons. Recent advancements in this field have focused on high-quality and comprehensive human reconstruction but often overlook the separation of clothing from the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Jingxuan Chen

Large-scale pre-trained vision-language models allow for the zero-shot text-based generation of 3D avatars. The previous state-of-the-art method utilized CLIP to supervise neural implicit models that reconstructed a human body mesh.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Shuo Huang , Zongxin Yang , Liangting Li , Yi Yang , Jia Jia

Creating high-fidelity 3D human head avatars is crucial for applications in VR/AR, digital human, and film production. Recent advances have leveraged morphable face models to generate animated head avatars from easily accessible data,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Yuelang Xu , Zhaoqi Su , Qingyao Wu , Yebin Liu

The creation of high-fidelity, digital versions of human heads is an important stepping stone in the process of further integrating virtual components into our everyday lives. Constructing such avatars is a challenging research problem, due…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Simon Giebenhain , Tobias Kirschstein , Martin Rünz , Lourdes Agapito , Matthias Nießner

Creating high-fidelity 3D head avatars has always been a research hotspot, but it remains a great challenge under lightweight sparse view setups. In this paper, we propose HHAvatar represented by controllable 3D Gaussians for high-fidelity…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Zhanfeng Liao , Yuelang Xu , Zhe Li , Qijing Li , Boyao Zhou , Ruifeng Bai , Di Xu , Hongwen Zhang , Yebin Liu

Deep generative models have been recently extended to synthesizing 3D digital humans. However, previous approaches treat clothed humans as a single chunk of geometry without considering the compositionality of clothing and accessories. As a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Taeksoo Kim , Shunsuke Saito , Hanbyul Joo

Recent advancements in 3D Gaussian Splatting (3DGS) have unlocked significant potential for modeling 3D head avatars, providing greater flexibility than mesh-based methods and more efficient rendering compared to NeRF-based approaches.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Peizhi Yan , Rabab Ward , Qiang Tang , Shan Du

In this work, we propose a novel clothed human reconstruction method called GaussianBody, based on 3D Gaussian Splatting. Compared with the costly neural radiance based models, 3D Gaussian Splatting has recently demonstrated great…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Mengtian Li , Shengxiang Yao , Zhifeng Xie , Keyu Chen

Realistic animatable human avatars from monocular videos are crucial for advancing human-robot interaction and enhancing immersive virtual experiences. While recent research on 3DGS-based human avatars has made progress, it still struggles…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Guangan Jiang , Tianzi Zhang , Dong Li , Zhenjun Zhao , Haoang Li , Mingrui Li , Hongyu Wang

Existing 3D clothed avatar reconstruction methods achieve high visual fidelity but ignore geometric structure and physical plausibility. They either model clothed humans as a single deformable surface or attempt garment disentanglement…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Daniel Eskandar , Berna Kabadayi , Garvita Tiwari , Gerard Pons-Moll

This paper aims to introduce 3D Gaussian for efficient, expressive, and editable digital avatar generation. This task faces two major challenges: (1) The unstructured nature of 3D Gaussian makes it incompatible with current generation…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Weitian Zhang , Yichao Yan , Yunhui Liu , Xingdong Sheng , Xiaokang Yang

This paper proposes an efficient 3D avatar coding framework that leverages compact human priors and canonical-to-target transformation to enable high-quality 3D human avatar video compression at ultra-low bit rates. The framework begins by…

Image and Video Processing · Electrical Eng. & Systems 2025-10-14 Shanzhi Yin , Bolin Chen , Xinju Wu , Ru-Ling Liao , Jie Chen , Shiqi Wang , Yan Ye

We present a universal prior model for 3D head avatars with explicit hair compositionality. Existing approaches to build generalizable priors for 3D head avatars often adopt a holistic modeling approach, treating the face and hair as an…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Byungjun Kim , Shunsuke Saito , Giljoo Nam , Tomas Simon , Jason Saragih , Hanbyul Joo , Junxuan Li

Recent studies have combined 3D Gaussian and 3D Morphable Models (3DMM) to construct high-quality 3D head avatars. In this line of research, existing methods either fail to capture the dynamic textures or incur significant overhead in terms…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Yating Wang , Xuan Wang , Ran Yi , Yanbo Fan , Jichen Hu , Jingcheng Zhu , Lizhuang Ma

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

This work addresses the problem of real-time rendering of photorealistic human body avatars learned from multi-view videos. While the classical approaches to model and render virtual humans generally use a textured mesh, recent research has…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Arthur Moreau , Jifei Song , Helisa Dhamo , Richard Shaw , Yiren Zhou , Eduardo Pérez-Pellitero

Recent advances in 3D Gaussian Splatting (3DGS) have enabled fast, photorealistic rendering of dynamic 3D scenes, showing strong potential in immersive communication. However, in digital human encoding and transmission, the compression…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haocheng Tang , Ruoke Yan , Xinhui Yin , Qi Zhang , Xinfeng Zhang , Siwei Ma , Wen Gao , Chuanmin Jia

Sparse volumetric reconstruction and rendering via 3D Gaussian splatting have recently enabled animatable 3D head avatars that are rendered under arbitrary viewpoints with impressive photorealism. Today, such photoreal avatars are seen as a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Gengyan Li , Paulo Gotardo , Timo Bolkart , Stephan Garbin , Kripasindhu Sarkar , Abhimitra Meka , Alexandros Lattas , Thabo Beeler

While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing methods for learning generative models of 3D humans with diverse…

Computer Vision and Pattern Recognition · Computer Science 2023-05-04 Zijian Dong , Xu Chen , Jinlong Yang , Michael J. Black , Otmar Hilliges , Andreas Geiger