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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

Audio-driven facial reenactment is a crucial technique that has a range of applications in film-making, virtual avatars and video conferences. Existing works either employ explicit intermediate face representations (e.g., 2D facial…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Ricong Huang , Peiwen Lai , Yipeng Qin , Guanbin Li

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

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

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

In this work, we present a new method for 3D face reconstruction from sparse-view RGB images. Unlike previous methods which are built upon 3D morphable models (3DMMs) with limited details, we leverage an implicit representation to encode…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Moran Li , Haibin Huang , Yi Zheng , Mengtian Li , Nong Sang , Chongyang Ma

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…

Active soft bodies can affect their shape through an internal actuation mechanism that induces a deformation. Similar to recent work, this paper utilizes a differentiable, quasi-static, and physics-based simulation layer to optimize for…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Lingchen Yang , Byungsoo Kim , Gaspard Zoss , Baran Gözcü , Markus Gross , Barbara Solenthaler

Implicit neural representation is a recent approach to learn shape collections as zero level-sets of neural networks, where each shape is represented by a latent code. So far, the focus has been shape reconstruction, while shape…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Matan Atzmon , David Novotny , Andrea Vedaldi , Yaron Lipman

Neural implicit fields are powerful for representing 3D scenes and generating high-quality novel views, but it remains challenging to use such implicit representations for creating a 3D human avatar with a specific identity and artistic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Ruixiang Jiang , Can Wang , Jingbo Zhang , Menglei Chai , Mingming He , Dongdong Chen , Jing Liao

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

We present the first deep implicit 3D morphable model (i3DMM) of full heads. Unlike earlier morphable face models it not only captures identity-specific geometry, texture, and expressions of the frontal face, but also models the entire…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Tarun Yenamandra , Ayush Tewari , Florian Bernard , Hans-Peter Seidel , Mohamed Elgharib , Daniel Cremers , Christian Theobalt

Neural fields such as implicit surfaces have recently enabled avatar modeling from raw scans without explicit temporal correspondences. In this work, we exploit autoregressive modeling to further extend this notion to capture dynamic…

Computer Vision and Pattern Recognition · Computer Science 2022-03-28 Ziqian Bai , Timur Bagautdinov , Javier Romero , Michael Zollhöfer , Ping Tan , Shunsuke Saito

The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved. Existing 3D representations either perform well in the realism of portrait images synthesis or…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Xiaochen Zhao , Lizhen Wang , Jingxiang Sun , Hongwen Zhang , Jinli Suo , Yebin Liu

Recently introduced implicit field representations offer an effective way of generating 3D object shapes. They leverage implicit decoder trained to take a 3D point coordinate concatenated with a shape encoding and to output a value which…

Computer Vision and Pattern Recognition · Computer Science 2021-10-13 Magdalena Proszewska , Marcin Mazur , Tomasz Trzciński , Przemysław Spurek

Implicit fields have recently shown increasing success in representing and learning 3D shapes accurately. Signed distance fields and occupancy fields are decades old and still the preferred representations, both with well-studied…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Edoardo Mello Rella , Ajad Chhatkuli , Ender Konukoglu , Luc Van Gool

This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene into a canonical neural radiance field and a set of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Sida Peng , Zhen Xu , Junting Dong , Qianqian Wang , Shangzhan Zhang , Qing Shuai , Hujun Bao , Xiaowei Zhou

We introduce a novel, data-driven approach for reconstructing temporally coherent 3D motion from unstructured and potentially partial observations of non-rigidly deforming shapes. Our goal is to achieve high-fidelity motion reconstructions…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Aymen Merrouche , Stefanie Wuhrer , Edmond Boyer

3D facial animation is often produced by manipulating facial deformation models (or rigs), that are traditionally parameterized by expression controls. A key component that is usually overlooked is expression 'style', as in, how a…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Lingchen Yang , Gaspard Zoss , Prashanth Chandran , Paulo Gotardo , Markus Gross , Barbara Solenthaler , Eftychios Sifakis , Derek Bradley

Neural implicit surface representations have recently emerged as popular alternative to explicit 3D object encodings, such as polygonal meshes, tabulated points, or voxels. While significant work has improved the geometric fidelity of these…

Graphics · Computer Science 2023-06-27 Yanran Guan , Andrei Chubarau , Ruby Rao , Derek Nowrouzezahrai
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