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Related papers: 360{\deg} Volumetric Portrait Avatar

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To address the ill-posed problem caused by partial observations in monocular human volumetric capture, we present AvatarCap, a novel framework that introduces animatable avatars into the capture pipeline for high-fidelity reconstruction in…

Computer Vision and Pattern Recognition · Computer Science 2022-07-13 Zhe Li , Zerong Zheng , Hongwen Zhang , Chaonan Ji , Yebin Liu

Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details. Neural volumetric representations approach photorealism but are hard to animate and do not…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Yufeng Zheng , Victoria Fernández Abrevaya , Marcel C. Bühler , Xu Chen , Michael J. Black , Otmar Hilliges

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…

Delivering immersive, 3D experiences for human communication requires a method to obtain 360 degree photo-realistic avatars of humans. To make these experiences accessible to all, only commodity hardware, like mobile phone cameras, should…

Computer Vision and Pattern Recognition · Computer Science 2022-10-24 Stanislaw Szymanowicz , Virginia Estellers , Tadas Baltrusaitis , Matthew Johnson

Acquisition and rendering of photo-realistic human heads is a highly challenging research problem of particular importance for virtual telepresence. Currently, the highest quality is achieved by volumetric approaches trained in a person…

Computer Vision and Pattern Recognition · Computer Science 2021-01-08 Amit Raj , Michael Zollhoefer , Tomas Simon , Jason Saragih , Shunsuke Saito , James Hays , Stephen Lombardi

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

Photorealistic 3D head avatars are vital for telepresence, gaming, and VR. However, most methods focus solely on facial regions, ignoring natural hand-face interactions, such as a hand resting on the chin or fingers gently touching the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haonan He , Yufeng Zheng , Jie Song

Immersive telepresence aims to transform human interaction in AR/VR applications by enabling lifelike full-body holographic representations for enhanced remote collaboration. However, existing systems rely on hardware-intensive multi-camera…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Fangyu Lin , Yingdong Hu , Zhening Liu , Yufan Zhuang , Zehong Lin , Jun Zhang

We propose FaceVR, a novel image-based method that enables video teleconferencing in VR based on self-reenactment. State-of-the-art face tracking methods in the VR context are focused on the animation of rigged 3d avatars. While they…

Computer Vision and Pattern Recognition · Computer Science 2018-03-23 Justus Thies , Michael Zollhöfer , Marc Stamminger , Christian Theobalt , Matthias Nießner

We present Vid2Avatar, a method to learn human avatars from monocular in-the-wild videos. Reconstructing humans that move naturally from monocular in-the-wild videos is difficult. Solving it requires accurately separating humans from…

Computer Vision and Pattern Recognition · Computer Science 2023-02-23 Chen Guo , Tianjian Jiang , Xu Chen , Jie Song , Otmar Hilliges

Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in AR or VR. Despite the progress, facial avatars reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Berna Kabadayi , Wojciech Zielonka , Bharat Lal Bhatnagar , Gerard Pons-Moll , Justus Thies

We present dynamic neural radiance fields for modeling the appearance and dynamics of a human face. Digitally modeling and reconstructing a talking human is a key building-block for a variety of applications. Especially, for telepresence…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Guy Gafni , Justus Thies , Michael Zollhöfer , Matthias Nießner

We present a unified framework for reconstructing animatable 3D human avatars from a single portrait across head, half-body, and full-body inputs. Our method tackles three bottlenecks: pose- and framing-sensitive feature representations,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jiawei Zhang , Lei Chu , Jiahao Li , Zhenyu Zang , Chong Li , Xiao Li , Xun Cao , Hao Zhu , Yan Lu

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

Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications. However, existing methods often struggle to model challenging facial…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Cong Wang , Di Kang , Yan-Pei Cao , Linchao Bao , Ying Shan , Song-Hai Zhang

We introduce FlexAvatar, a method for creating high-quality and complete 3D head avatars from a single image. A core challenge lies in the limited availability of multi-view data and the tendency of monocular training to yield incomplete 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Tobias Kirschstein , Simon Giebenhain , Matthias Nießner

We present Vid2Avatar-Pro, a method to create photorealistic and animatable 3D human avatars from monocular in-the-wild videos. Building a high-quality avatar that supports animation with diverse poses from a monocular video is challenging…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Chen Guo , Junxuan Li , Yash Kant , Yaser Sheikh , Shunsuke Saito , Chen Cao

Immersive VR telepresence ideally means being able to interact and communicate with digital avatars that are indistinguishable from and precisely reflect the behaviour of their real counterparts. The core technical challenge is two fold:…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Jianchun Chen , Jian Wang , Yinda Zhang , Rohit Pandey , Thabo Beeler , Marc Habermann , Christian Theobalt

Reconstructing photorealistic and dynamic portrait avatars from images is essential to many applications including advertising, visual effects, and virtual reality. Depending on the application, avatar reconstruction involves different…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Felix Taubner , Ruihang Zhang , Mathieu Tuli , David B. Lindell

360{\deg} cameras can capture complete environments in a single shot, which makes 360{\deg} imagery alluring in many computer vision tasks. However, monocular depth estimation remains a challenge for 360{\deg} data, particularly for high…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Manuel Rey-Area , Mingze Yuan , Christian Richardt
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