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Related papers: 3DRealHead: Few-Shot Detailed Head Avatar

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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

In this work, we introduce a novel high-fidelity 3D head reconstruction method from a single portrait image, regardless of perspective, expression, or accessories. Despite significant efforts in adapting 2D generative models for novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Jianfu Zhang , Yujie Gao , Jiahui Zhan , Wentao Wang , Yiyi Zhang , Haohua Zhao , Liqing Zhang

Faithful real-time facial animation is essential for avatar-mediated telepresence in Virtual Reality (VR). To emulate authentic communication, avatar animation needs to be efficient and accurate: able to capture both extreme and subtle…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Shaojie Bai , Te-Li Wang , Chenghui Li , Akshay Venkatesh , Tomas Simon , Chen Cao , Gabriel Schwartz , Ryan Wrench , Jason Saragih , Yaser Sheikh , Shih-En Wei

We present X-Avatar, a novel avatar model that captures the full expressiveness of digital humans to bring about life-like experiences in telepresence, AR/VR and beyond. Our method models bodies, hands, facial expressions and appearance in…

Computer Vision and Pattern Recognition · Computer Science 2023-03-10 Kaiyue Shen , Chen Guo , Manuel Kaufmann , Juan Jose Zarate , Julien Valentin , Jie Song , Otmar Hilliges

There is a growing demand for the accessible creation of high-quality 3D avatars that are animatable and customizable. Although 3D morphable models provide intuitive control for editing and animation, and robustness for single-view face…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Connor Z. Lin , Koki Nagano , Jan Kautz , Eric R. Chan , Umar Iqbal , Leonidas Guibas , Gordon Wetzstein , Sameh Khamis

We propose 360{\deg} Volumetric Portrait (3VP) Avatar, a novel method for reconstructing 360{\deg} photo-realistic portrait avatars of human subjects solely based on monocular video inputs. State-of-the-art monocular avatar reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Jalees Nehvi , Berna Kabadayi , Julien Valentin , Justus Thies

Recent advances in full-head reconstruction have been obtained by optimizing a neural field through differentiable surface or volume rendering to represent a single scene. While these techniques achieve an unprecedented accuracy, they take…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Antonio Canela , Pol Caselles , Ibrar Malik , Eduard Ramon , Jaime García , Jordi Sánchez-Riera , Gil Triginer , Francesc Moreno-Noguer

While high fidelity and efficiency are central to the creation of digital head avatars, recent methods relying on 2D or 3D generative models often experience limitations such as shape distortion, expression inaccuracy, and identity…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Xiaochen Zhao , Jingxiang Sun , Lizhen Wang , Jinli Suo , Yebin Liu

We present an approach for the reconstruction of textured 3D meshes of human heads from one or few views. Since such few-shot reconstruction is underconstrained, it requires prior knowledge which is hard to impose on traditional 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Egor Burkov , Ruslan Rakhimov , Aleksandr Safin , Evgeny Burnaev , Victor Lempitsky

Several recent works have shown how highly realistic human head images can be obtained by training convolutional neural networks to generate them. In order to create a personalized talking head model, these works require training on a large…

Computer Vision and Pattern Recognition · Computer Science 2019-12-17 Egor Zakharov , Aliaksandra Shysheya , Egor Burkov , Victor Lempitsky

The recent state of the art on monocular 3D face reconstruction from image data has made some impressive advancements, thanks to the advent of Deep Learning. However, it has mostly focused on input coming from a single RGB image,…

Computer Vision and Pattern Recognition · Computer Science 2022-07-25 Panagiotis P. Filntisis , George Retsinas , Foivos Paraperas-Papantoniou , Athanasios Katsamanis , Anastasios Roussos , Petros Maragos

We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achieve user-controlled facial expressions and head poses. Our…

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

High-quality reconstruction of controllable 3D head avatars from 2D videos is highly desirable for virtual human applications in movies, games, and telepresence. Neural implicit fields provide a powerful representation to model 3D head…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Chuhan Chen , Matthew O'Toole , Gaurav Bharaj , Pablo Garrido

With the booming of virtual reality (VR) technology, there is a growing need for customized 3D avatars. However, traditional methods for 3D avatar modeling are either time-consuming or fail to retain similarity to the person being modeled.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Chuanyu Pan , Guowei Yang , Taijiang Mu , Yu-Kun Lai

Facial expression retargeting from humans to virtual characters is a useful technique in computer graphics and animation. Traditional methods use markers or blendshapes to construct a mapping between the human and avatar faces. However,…

Computer Vision and Pattern Recognition · Computer Science 2020-08-13 Juyong Zhang , Keyu Chen , Jianmin Zheng

Motion transfer of talking-head videos involves generating a new video with the appearance of a subject video and the motion pattern of a driving video. Current methodologies primarily depend on a limited number of subject images and 2D…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Haomiao Ni , Jiachen Liu , Yuan Xue , Sharon X. Huang

Generating talking head videos through a face image and a piece of speech audio still contains many challenges. ie, unnatural head movement, distorted expression, and identity modification. We argue that these issues are mainly because of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Wenxuan Zhang , Xiaodong Cun , Xuan Wang , Yong Zhang , Xi Shen , Yu Guo , Ying Shan , Fei Wang

We propose a method to build in real-time animated 3D head models using a consumer-grade RGB-D camera. Our proposed method is the first one to provide simultaneously comprehensive facial motion tracking and a detailed 3D model of the user's…

Computer Vision and Pattern Recognition · Computer Science 2020-04-23 Diego Thomas

In this paper, we present our framework for neural face/head reenactment whose goal is to transfer the 3D head orientation and expression of a target face to a source face. Previous methods focus on learning embedding networks for identity…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Stella Bounareli , Christos Tzelepis , Vasileios Argyriou , Ioannis Patras , Georgios Tzimiropoulos