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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 propose FlashAvatar, a novel and lightweight 3D animatable avatar representation that could reconstruct a digital avatar from a short monocular video sequence in minutes and render high-fidelity photo-realistic images at 300FPS on a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jun Xiang , Xuan Gao , Yudong Guo , Juyong Zhang

3D Gaussian Splatting (3DGS) provides an efficient method for high-quality scene reconstruction using anisotropic Gaussians. Recently, 3DGS-based methods have significantly improved the rendering quality of human avatars while enabling…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Hongzhe Liao , Chuhua Xian , Hongmin Cai , Haiyang Liu , Fa-Ting Hong

In this paper, we propose Generalizable and Animatable Gaussian head Avatar (GAGAvatar) for one-shot animatable head avatar reconstruction. Existing methods rely on neural radiance fields, leading to heavy rendering consumption and low…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Xuangeng Chu , Tatsuya Harada

We introduce GaussianAvatars, a new method to create photorealistic head avatars that are fully controllable in terms of expression, pose, and viewpoint. The core idea is a dynamic 3D representation based on 3D Gaussian splats that are…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Shenhan Qian , Tobias Kirschstein , Liam Schoneveld , Davide Davoli , Simon Giebenhain , Matthias Nießner

We propose GGAvatar, a novel 3D avatar representation designed to robustly model dynamic head avatars with complex identities and deformations. GGAvatar employs a coarse-to-fine structure, featuring two core modules: Neutral Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Xinyang Li , Jiaxin Wang , Yixin Xuan , Gongxin Yao , Yu Pan

Gaussian splatting has emerged as a powerful 3D representation that harnesses the advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper, we seek to leverage Gaussian splatting to generate realistic…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Ye Yuan , Xueting Li , Yangyi Huang , Shalini De Mello , Koki Nagano , Jan Kautz , Umar Iqbal

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

The ability to animate photo-realistic head avatars reconstructed from monocular portrait video sequences represents a crucial step in bridging the gap between the virtual and real worlds. Recent advancements in head avatar techniques,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yufan Chen , Lizhen Wang , Qijing Li , Hongjiang Xiao , Shengping Zhang , Hongxun Yao , Yebin Liu

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

We introduce HyperGaussians, a novel extension of 3D Gaussian Splatting for high-quality animatable face avatars. Creating such detailed face avatars from videos is a challenging problem and has numerous applications in augmented and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Gent Serifi , Marcel C. Buehler

Neural radiance fields are capable of reconstructing high-quality drivable human avatars but are expensive to train and render and not suitable for multi-human scenes with complex shadows. To reduce consumption, we propose Animatable 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Yang Liu , Xiang Huang , Minghan Qin , Qinwei Lin , Haoqian Wang

Generating animatable human avatars from a single image is essential for various digital human modeling applications. Existing 3D reconstruction methods often struggle to capture fine details in animatable models, while generative…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Lingteng Qiu , Shenhao Zhu , Qi Zuo , Xiaodong Gu , Yuan Dong , Junfei Zhang , Chao Xu , Zhe Li , Weihao Yuan , Liefeng Bo , Guanying Chen , Zilong Dong

In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA). Our innovation lies in addressing the intricate challenges of delivering high-fidelity human body…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Xinqi Liu , Chenming Wu , Jialun Liu , Xing Liu , Jinbo Wu , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang

Despite recent progress in 3D head avatar generation, balancing identity preservation, i.e., reconstruction, with novel poses and expressions, i.e., animation, remains a challenge. Existing methods struggle to adapt Gaussians to varying…

Graphics · Computer Science 2025-07-25 SeungJun Moon , Hah Min Lew , Seungeun Lee , Ji-Su Kang , Gyeong-Moon Park

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

This paper presents a Surface-Aligned Gaussian representation for creating animatable human avatars from monocular videos,aiming at improving the novel view and pose synthesis performance while ensuring fast training and real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Ronghan Chen , Yang Cong , Jiayue Liu

Although neural rendering has made significant advances in creating lifelike, animatable full-body and head avatars, incorporating detailed expressions into full-body avatars remains largely unexplored. We present DEGAS, the first 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhijing Shao , Duotun Wang , Qing-Yao Tian , Yao-Dong Yang , Hengyu Meng , Zeyu Cai , Bo Dong , Yu Zhang , Kang Zhang , Zeyu Wang

Facial expression and hand motions are necessary to express our emotions and interact with the world. Nevertheless, most of the 3D human avatars modeled from a casually captured video only support body motions without facial expressions and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Gyeongsik Moon , Takaaki Shiratori , Shunsuke Saito

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