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Related papers: i3DMM: Deep Implicit 3D Morphable Model of Human H…

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Over the last years, 3D morphable models (3DMMs) have emerged as a state-of-the-art methodology for modeling and generating expressive 3D avatars. However, given their reliance on a strict topology, along with their linear nature, they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Rolandos Alexandros Potamias , Stathis Galanakis , Jiankang Deng , Athanasios Papaioannou , Stefanos Zafeiriou

Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears,…

Computer Vision and Pattern Recognition · Computer Science 2020-02-21 Stylianos Ploumpis , Evangelos Ververas , Eimear O' Sullivan , Stylianos Moschoglou , Haoyang Wang , Nick Pears , William A. P. Smith , Baris Gecer , Stefanos Zafeiriou

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

Precise representations of 3D faces are beneficial to various computer vision and graphics applications. Due to the data discretization and model linearity, however, it remains challenging to capture accurate identity and expression clues…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Mingwu Zheng , Hongyu Yang , Di Huang , Liming Chen

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

Accurate representations of 3D faces are of paramount importance in various computer vision and graphics applications. However, the challenges persist due to the limitations imposed by data discretization and model linearity, which hinder…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Mingwu Zheng , Haiyu Zhang , Hongyu Yang , Liming Chen , Di Huang

3D Morphable models of the human body capture variations among subjects and are useful in reconstruction and editing applications. Current dental models use an explicit mesh scene representation and model only the teeth, ignoring the gum.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Congyi Zhang , Mohamed Elgharib , Gereon Fox , Min Gu , Christian Theobalt , Wenping Wang

We propose a novel 3D morphable model for complete human heads based on hybrid neural fields. At the core of our model lies a neural parametric representation that disentangles identity and expressions in disjoint latent spaces. To this…

Computer Vision and Pattern Recognition · Computer Science 2023-04-17 Simon Giebenhain , Tobias Kirschstein , Markos Georgopoulos , Martin Rünz , Lourdes Agapito , Matthias Nießner

Recovery of a 3D head model including the complete face and hair regions is still a challenging problem in computer vision and graphics. In this paper, we consider this problem using only a few multi-view portrait images as input. Previous…

Computer Vision and Pattern Recognition · Computer Science 2021-10-05 Xueying Wang , Yudong Guo , Zhongqi Yang , Juyong Zhang

Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D surfaces of an object class. In this context, we identify an interesting question that has previously not received research attention: is it…

Computer Vision and Pattern Recognition · Computer Science 2019-03-12 Stylianos Ploumpis , Haoyang Wang , Nick Pears , William A. P. Smith , Stefanos Zafeiriou

3D Morphable Model (3DMM) fitting has widely benefited face analysis due to its strong 3D priori. However, previous reconstructed 3D faces suffer from degraded visual verisimilitude due to the loss of fine-grained geometry, which is…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Xiangyu Zhu , Chang Yu , Di Huang , Zhen Lei , Hao Wang , Stan Z. Li

3D morphable models (3DMMs) are a powerful tool to represent the possible shapes and appearances of an object category. Given a single test image, 3DMMs can be used to solve various tasks, such as predicting the 3D shape, pose, semantic…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Leonhard Sommer , Olaf Dünkel , Christian Theobalt , Adam Kortylewski

As a classic statistical model of 3D facial shape and texture, 3D Morphable Model (3DMM) is widely used in facial analysis, e.g., model fitting, image synthesis. Conventional 3DMM is learned from a set of well-controlled 2D face images with…

Computer Vision and Pattern Recognition · Computer Science 2018-08-28 Luan Tran , Xiaoming Liu

Implicit functions represented as deep learning approximations are powerful for reconstructing 3D surfaces. However, they can only produce static surfaces that are not controllable, which provides limited ability to modify the resulting…

Computer Vision and Pattern Recognition · Computer Science 2021-11-29 Bharat Lal Bhatnagar , Cristian Sminchisescu , Christian Theobalt , Gerard Pons-Moll

The 3D Morphable Model (3DMM) is a powerful statistical tool for representing 3D face shapes. To build a 3DMM, a training set of face scans in full point-to-point correspondence is required, and its modeling capabilities directly depend on…

Computer Vision and Pattern Recognition · Computer Science 2021-06-25 Claudio Ferrari , Stefano Berretti , Pietro Pala , Alberto Del Bimbo

We present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-based predecessor, our model employs implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Maximilian Weiherer , Antonia von Riedheim , Vanessa Brébant , Bernhard Egger , Christoph Palm

Recent 3D face reconstruction methods reconstruct the entire head compared to earlier approaches which only model the face. Although these methods accurately reconstruct facial features, they do not explicitly regulate the upper part of the…

Computer Vision and Pattern Recognition · Computer Science 2022-08-26 Sohan Anisetty , Varsha Saravanabavan , Cai Yiyu

Undoubtedly, high-fidelity 3D hair plays an indispensable role in digital humans. However, existing monocular hair modeling methods are either tricky to deploy in digital systems (e.g., due to their dependence on complex user interactions…

Graphics · Computer Science 2022-05-10 Keyu Wu , Yifan Ye , Lingchen Yang , Hongbo Fu , Kun Zhou , Youyi Zheng

3D Morphable Models (3DMMs) have played a pivotal role as a fundamental representation or initialization for 3D avatar animation and reconstruction. However, extending 3DMMs to hair remains challenging due to the difficulty of enforcing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zidu Wang , Jiankuo Zhao , Miao Xu , Xiangyu Zhu , Zhen Lei

We propose ID-to-3D, a method to generate identity- and text-guided 3D human heads with disentangled expressions, starting from even a single casually captured in-the-wild image of a subject. The foundation of our approach is anchored in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Francesca Babiloni , Alexandros Lattas , Jiankang Deng , Stefanos Zafeiriou
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