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Related papers: Nonlinear 3D Face Morphable Model

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In this paper we present, to the best of our knowledge, the first method to learn a generative model of 3D shapes from natural images in a fully unsupervised way. For example, we do not use any ground truth 3D or 2D annotations, stereo…

Computer Vision and Pattern Recognition · Computer Science 2019-10-02 Attila Szabó , Givi Meishvili , Paolo Favaro

We present a simple yet effective general-purpose framework for modeling 3D shapes by leveraging recent advances in 2D image generation using CNNs. Using just a single depth image of the object, we can output a dense multi-view depth map…

Computer Vision and Pattern Recognition · Computer Science 2020-09-08 Kamal Gupta , Susmija Jabbireddy , Ketul Shah , Abhinav Shrivastava , Matthias Zwicker

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

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

In computer-aided design (CAD) systems, 2D line drawings are commonly used to illustrate 3D object designs. To reconstruct the 3D models depicted by a single 2D line drawing, an important key is finding the edge loops in the line drawing…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Kehan Wang , Jia Zheng , Zihan Zhou

Recent advances in 3D face stylization have made significant strides in few to zero-shot settings. However, the degree of stylization achieved by existing methods is often not sufficient for practical applications because they are mostly…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Soyeon Yoon , Kwan Yun , Kwanggyoon Seo , Sihun Cha , Jung Eun Yoo , Junyong Noh

Monocular 3D face reconstruction is a wide-spread topic, and existing approaches tackle the problem either through fast neural network inference or offline iterative reconstruction of face geometry. In either case carefully-designed energy…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Christopher Otto , Prashanth Chandran , Gaspard Zoss , Markus Gross , Paulo Gotardo , Derek Bradley

An efficient, fully automatic method for 3D face shape and pose estimation in unconstrained 2D imagery is presented. The proposed method jointly estimates a dense set of 3D landmarks and facial geometry using a single pass of a modified…

Computer Vision and Pattern Recognition · Computer Science 2017-08-31 Daniel Crispell , Maxim Bazik

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 address the 3D reconstruction of human faces from a single RGB image. To this end, we propose Pixel3DMM, a set of highly-generalized vision transformers which predict per-pixel geometric cues in order to constrain the optimization of a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Simon Giebenhain , Tobias Kirschstein , Martin Rünz , Lourdes Agapito , Matthias Nießner

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

Existing face aging methods often focus on modeling either texture aging or using an entangled shape-texture representation to achieve face aging. However, shape and texture are two distinct factors that mutually affect the human face aging…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Qianrui Teng , Rui Wang , Xing Cui , Peipei Li , Zhaofeng He

Many recent works have reconstructed distinctive 3D face shapes by aggregating shape parameters of the same identity and separating those of different people based on parametric models (e.g., 3D morphable models (3DMMs)). However, despite…

Computer Vision and Pattern Recognition · Computer Science 2021-12-28 Diqiong Jiang , Yiwei Jin , Fanglue Zhang , Yukun Yai , Risheng Deng , Ruofeng Tong , Min Tang

Fast and robust three-dimensional reconstruction of facial geometric structure from a single image is a challenging task with numerous applications. Here, we introduce a learning-based approach for reconstructing a three-dimensional face…

Computer Vision and Pattern Recognition · Computer Science 2016-09-27 Elad Richardson , Matan Sela , Ron Kimmel

We introduce a novel learning-based method for encoding and manipulating 3D surface meshes. Our method is specifically designed to create an interpretable embedding space for deformable shape collections. Unlike previous 3D mesh…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Sara Hahner , Souhaib Attaiki , Jochen Garcke , Maks Ovsjanikov

3D-controllable portrait synthesis has significantly advanced, thanks to breakthroughs in generative adversarial networks (GANs). However, it is still challenging to manipulate existing face images with precise 3D control. While…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Yuchen Liu , Zhixin Shu , Yijun Li , Zhe Lin , Richard Zhang , S. Y. Kung

3D face reconstruction from a single 2D image is a very important topic in computer vision. However, the current reconstruction methods are usually non-sensitive to face identities and over-sensitive to facial poses, which may result in…

Computer Vision and Pattern Recognition · Computer Science 2019-05-17 Yao Luo , Xiaoguang Tu , Mei Xie

This paper introduces a model for producing stylized line drawings from 3D shapes. The model takes a 3D shape and a viewpoint as input, and outputs a drawing with textured strokes, with variations in stroke thickness, deformation, and color…

Computer Vision and Pattern Recognition · Computer Science 2021-10-11 Difan Liu , Matthew Fisher , Aaron Hertzmann , Evangelos Kalogerakis

This paper presents a novel image inpainting framework for face mask removal. Although current methods have demonstrated their impressive ability in recovering damaged face images, they suffer from two main problems: the dependence on…

Computer Vision and Pattern Recognition · Computer Science 2022-03-04 Xiangnan Yin , Liming Chen

In this paper, we present a novel open-source pipeline for face registration based on Gaussian processes as well as an application to face image analysis. Non-rigid registration of faces is significant for many applications in computer…

Computer Vision and Pattern Recognition · Computer Science 2017-09-27 Thomas Gerig , Andreas Morel-Forster , Clemens Blumer , Bernhard Egger , Marcel Lüthi , Sandro Schönborn , Thomas Vetter