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3D head animation has seen major quality and runtime improvements over the last few years, particularly empowered by the advances in differentiable rendering and neural radiance fields. Real-time rendering is a highly desirable goal for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Helisa Dhamo , Yinyu Nie , Arthur Moreau , Jifei Song , Richard Shaw , Yiren Zhou , Eduardo Pérez-Pellitero

Creating photorealistic 3D head avatars from limited input has become increasingly important for applications in virtual reality, telepresence, and digital entertainment. While recent advances like neural rendering and 3D Gaussian splatting…

Graphics · Computer Science 2026-03-12 Chen Guo , Zhuo Su , Liao Wang , Jian Wang , Shuang Li , Xu Chang , Zhaohu Li , Yang Zhao , Guidong Wang , Yebin Liu , Ruqi Huang

Recent advancements in 3D Gaussian Splatting (3DGS) have unlocked significant potential for modeling 3D head avatars, providing greater flexibility than mesh-based methods and more efficient rendering compared to NeRF-based approaches.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Peizhi Yan , Rabab Ward , Qiang Tang , Shan Du

Head avatar reenactment focuses on creating animatable personal avatars from monocular videos, serving as a foundational element for applications like social signal understanding, gaming, human-machine interaction, and computer vision.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Wei Liang , Hui Yu , Derui Ding , Rachael E. Jack , Philippe G. Schyns

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

Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynamic performances is to track the underlying geometry using a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Kartik Teotia , Mallikarjun B R , Xingang Pan , Hyeongwoo Kim , Pablo Garrido , Mohamed Elgharib , Christian Theobalt

In order to be widely applicable, speech-driven 3D head avatars must articulate their lips in accordance with speech, while also conveying the appropriate emotions with dynamically changing facial expressions. The key problem is that…

Graphics · Computer Science 2026-01-28 Radek Daněček , Carolin Schmitt , Senya Polikovsky , Michael J. Black

In this paper, we rethink text-to-avatar generative models by proposing TeRA, a more efficient and effective framework than the previous SDS-based models and general large 3D generative models. Our approach employs a two-stage training…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Yanwen Wang , Yiyu Zhuang , Jiawei Zhang , Li Wang , Yifei Zeng , Xun Cao , Xinxin Zuo , Hao Zhu

Existing methods for image-to-3D avatar generation struggle to produce highly detailed, animation-ready avatars suitable for real-world applications. We introduce AdaHuman, a novel framework that generates high-fidelity animatable 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Yangyi Huang , Ye Yuan , Xueting Li , Jan Kautz , Umar Iqbal

We present HAHA - a novel approach for animatable human avatar generation from monocular input videos. The proposed method relies on learning the trade-off between the use of Gaussian splatting and a textured mesh for efficient and high…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 David Svitov , Pietro Morerio , Lourdes Agapito , Alessio Del Bue

We present DreamHuman, a method to generate realistic animatable 3D human avatar models solely from textual descriptions. Recent text-to-3D methods have made considerable strides in generation, but are still lacking in important aspects.…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Nikos Kolotouros , Thiemo Alldieck , Andrei Zanfir , Eduard Gabriel Bazavan , Mihai Fieraru , Cristian Sminchisescu

Animating human face images aims to synthesize a desired source identity in a natural-looking way mimicking a driving video's facial movements. In this context, Generative Adversarial Networks have demonstrated remarkable potential in…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Alireza Javanmardi , Alain Pagani , Didier Stricker

Diffusion models have shown impressive potential on talking head generation. While plausible appearance and talking effect are achieved, these methods still suffer from temporal, 3D or expression inconsistency due to the error accumulation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

To the best of our knowledge, we first present a live system that generates personalized photorealistic talking-head animation only driven by audio signals at over 30 fps. Our system contains three stages. The first stage is a deep neural…

Graphics · Computer Science 2021-09-27 Yuanxun Lu , Jinxiang Chai , Xun Cao

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 introduce a framework that automates the transformation of static anime illustrations into manipulatable 2.5D models. Current professional workflows require tedious manual segmentation and the artistic ``hallucination'' of occluded…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Jian Lin , Chengze Li , Haoyun Qin , Kwun Wang Chan , Yanghua Jin , Hanyuan Liu , Stephen Chun Wang Choy , Xueting Liu

Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xiyi Chen , Marko Mihajlovic , Shaofei Wang , Sergey Prokudin , Siyu Tang

When people deliver a speech, they naturally move heads, and this rhythmic head motion conveys prosodic information. However, generating a lip-synced video while moving head naturally is challenging. While remarkably successful, existing…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Lele Chen , Guofeng Cui , Celong Liu , Zhong Li , Ziyi Kou , Yi Xu , Chenliang Xu

Talking head synthesis, an advanced method for generating portrait videos from a still image driven by specific content, has garnered widespread attention in virtual reality, augmented reality and game production. Recently, significant…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Ming Meng , Yufei Zhao , Bo Zhang , Yonggui Zhu , Weimin Shi , Maxwell Wen , Zhaoxin Fan

Sparse volumetric reconstruction and rendering via 3D Gaussian splatting have recently enabled animatable 3D head avatars that are rendered under arbitrary viewpoints with impressive photorealism. Today, such photoreal avatars are seen as a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Gengyan Li , Paulo Gotardo , Timo Bolkart , Stephan Garbin , Kripasindhu Sarkar , Abhimitra Meka , Alexandros Lattas , Thabo Beeler