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Related papers: VASA-3D: Lifelike Audio-Driven Gaussian Head Avata…

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Reconstructing high-fidelity 3D head avatars is crucial in various applications such as virtual reality. The pioneering methods reconstruct realistic head avatars with Neural Radiance Fields (NeRF), which have been limited by training and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Peng Chen , Xiaobao Wei , Qingpo Wuwu , Xinyi Wang , Xingyu Xiao , Ming Lu

The ability to create realistic, animatable and relightable head avatars from casual video sequences would open up wide ranging applications in communication and entertainment. Current methods either build on explicit 3D morphable meshes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Yufeng Zheng , Wang Yifan , Gordon Wetzstein , Michael J. Black , Otmar Hilliges

We propose HeadsUp, a scalable feed-forward method for reconstructing high-quality 3D Gaussian heads from large-scale multi-camera setups. Our method employs an efficient encoder-decoder architecture that compresses input views into a…

In this paper, we propose a novel audio-driven talking head method capable of simultaneously generating highly expressive facial expressions and hand gestures. Unlike existing methods that focus on generating full-body or half-body poses,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Linrui Tian , Siqi Hu , Qi Wang , Bang Zhang , Liefeng Bo

Personalized 3D avatars require an animatable representation of digital humans. Doing so instantly from monocular videos offers scalability to broad class of users and wide-scale applications. In this paper, we present a fast, simple, yet…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Pramish Paudel , Anubhav Khanal , Ajad Chhatkuli , Danda Pani Paudel , Jyoti Tandukar

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

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

Talking head generation is increasingly important in virtual reality (VR), especially for social scenarios involving multi-turn conversation. Existing approaches face notable limitations: mesh-based 3D methods can model dual-person dialogue…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Peng Chen , Xiaobao Wei , Yi Yang , Naiming Yao , Hui Chen , Feng Tian

The manipulation of latent space has recently become an interesting topic in the field of generative models. Recent research shows that latent directions can be used to manipulate images towards certain attributes. However, controlling the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Zehranaz Canfes , M. Furkan Atasoy , Alara Dirik , Pinar Yanardag

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

We propose GaussianTalker, a novel framework for real-time generation of pose-controllable talking heads. It leverages the fast rendering capabilities of 3D Gaussian Splatting (3DGS) while addressing the challenges of directly controlling…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Kyusun Cho , Joungbin Lee , Heeji Yoon , Yeobin Hong , Jaehoon Ko , Sangjun Ahn , Seungryong Kim

We present a novel framework for animating humans in 3D scenes using 3D Gaussian Splatting (3DGS), a neural scene representation that has recently achieved state-of-the-art photorealistic results for novel-view synthesis but remains…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Aymen Mir , Jian Wang , Riza Alp Guler , Chuan Guo , Gerard Pons-Moll , Bing Zhou

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

This paper presents EGSTalker, a real-time audio-driven talking head generation framework based on 3D Gaussian Splatting (3DGS). Designed to enhance both speed and visual fidelity, EGSTalker requires only 3-5 minutes of training video to…

Sound · Computer Science 2025-10-13 Tianheng Zhu , Yinfeng Yu , Liejun Wang , Fuchun Sun , Wendong Zheng

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

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

We present FastAvatar, a fast and robust algorithm for single-image 3D face reconstruction using 3D Gaussian Splatting (3DGS). Given a single input image from an arbitrary pose, FastAvatar recovers a high-quality, full-head 3DGS avatar in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Hao Liang , Zhixuan Ge , Soumendu Majee , Ashish Tiwari , G. M. Dilshan Godaliyadda , Ashok Veeraraghavan , Guha Balakrishnan

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

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

While recent 3D head avatar creation methods attempt to animate facial dynamics, they often fail to capture personalized details, limiting realism and expressiveness. To fill this gap, we present DipGuava (Disentangled and Personalized…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Jeonghaeng Lee , Seok Keun Choi , Zhixuan Li , Weisi Lin , Sanghoon Lee
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