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High-quality, animatable 3D human avatar reconstruction from monocular videos offers significant potential for reducing reliance on complex hardware, making it highly practical for applications in game development, augmented reality, and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Xia Yuan , Hai Yuan , Wenyi Ge , Ying Fu , Xi Wu , Guanyu Xing

With the rapid advancement of 3D representation techniques and generative models, substantial progress has been made in reconstructing full-body 3D avatars from a single image. However, this task remains fundamentally ill-posedness due to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Gaofeng Liu , Hengsen Li , Ruoyu Gao , Xuetong Li , Zhiyuan Ma , Tao Fang

We present MoGA, a novel method to reconstruct high-fidelity 3D Gaussian avatars from a single-view image. The main challenge lies in inferring unseen appearance and geometric details while ensuring 3D consistency and realism. Most previous…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zijian Dong , Longteng Duan , Jie Song , Michael J. Black , Andreas Geiger

Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision and graphics. While existing 3D human avatar modeling approaches can effectively capture…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Yuze Su , Hongsong Wang , Jie Gui , Liang Wang

Creating high-quality animatable 3D human avatars from a single image remains a significant challenge in computer vision due to the inherent difficulty of reconstructing complete 3D information from a single viewpoint. Current approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Yonwoo Choi

We present a generalizable feed-forward Gaussian splatting framework for human 3D reconstruction and real-time animation that operates directly on multi-view RGB images and their associated SMPL-X poses. Unlike prior methods that rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Devdoot Chatterjee , Zakaria Laskar , C. V. Jawahar

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

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

3D Gaussian Splatting (3DGS) has enabled photorealistic and real-time rendering of 3D head avatars. Existing 3DGS-based avatars typically rely on tens of thousands of 3D Gaussian points (Gaussians), with the number of Gaussians fixed after…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Peizhi Yan , Rabab Ward , Qiang Tang , Shan Du

In practical real-time XR and telepresence applications, network and computing resources fluctuate frequently. Therefore, a progressive 3D representation is needed. To this end, we propose ProgressiveAvatars, a progressive avatar…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Kaiwen Song , Jinkai Cui , Juyong Zhang

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

We introduce an approach that creates animatable human avatars from monocular videos using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields (NeRFs) achieve high-quality novel-view/novel-pose image synthesis but…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Zhiyin Qian , Shaofei Wang , Marko Mihajlovic , Andreas Geiger , Siyu Tang

Recent advances in neural radiance fields enable novel view synthesis of photo-realistic images in dynamic settings, which can be applied to scenarios with human animation. Commonly used implicit backbones to establish accurate models,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 HyunJun Jung , Nikolas Brasch , Jifei Song , Eduardo Perez-Pellitero , Yiren Zhou , Zhihao Li , Nassir Navab , Benjamin Busam

Despite recent progress in 3D Gaussian-based head avatar modeling, efficiently generating high fidelity avatars remains a challenge. Current methods typically rely on extensive multi-view capture setups or monocular videos with per-identity…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Xinya Ji , Sebastian Weiss , Manuel Kansy , Jacek Naruniec , Xun Cao , Barbara Solenthaler , Derek Bradley

We present a novel framework for generating high-quality, animatable 4D avatar from a single image. While recent advances have shown promising results in 4D avatar creation, existing methods either require extensive multiview data or…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Fei Yin , Mallikarjun B R , Chun-Han Yao , Rafał Mantiuk , Varun Jampani

Inspired by the effectiveness of 3D Gaussian Splatting (3DGS) in reconstructing detailed 3D scenes within multi-view setups and the emergence of large 2D human foundation models, we introduce Arc2Avatar, the first SDS-based method utilizing…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Dimitrios Gerogiannis , Foivos Paraperas Papantoniou , Rolandos Alexandros Potamias , Alexandros Lattas , Stefanos Zafeiriou

Audio-driven talking head generation is a core component of digital avatars, and 3D Gaussian Splatting has shown strong performance in real-time rendering of high-fidelity talking heads. However, achieving precise control over fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Shaoyang Xie , Xiaofeng Cong , Baosheng Yu , Zhipeng Gui , Jie Gui , Yuan Yan Tang , James Tin-Yau Kwok

We introduce a novel approach to creating ultra-realistic head avatars and rendering them in real-time (>30fps at $2048 \times 1334$ resolution). First, we propose a hybrid explicit representation that combines the advantages of two…

Graphics · Computer Science 2025-02-20 Hongrui Cai , Yuting Xiao , Xuan Wang , Jiafei Li , Yudong Guo , Yanbo Fan , Shenghua Gao , Juyong Zhang

Reconstructing high-fidelity and animatable 3D head avatars from monocular videos remains a challenging yet essential task. Existing methods based on 3D Gaussian Splatting typically bind Gaussians to mesh triangles and model deformations…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Jiankuo Zhao , Xiangyu Zhu , Zidu Wang , Zhen Lei

Creating and customizing a 3D clothed avatar from textual descriptions is a critical and challenging task. Traditional methods often treat the human body and clothing as inseparable, limiting users' ability to freely mix and match garments.…

Graphics · Computer Science 2025-03-18 Jia Gong , Shenyu Ji , Lin Geng Foo , Kang Chen , Hossein Rahmani , Jun Liu
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