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Related papers: Towards Realistic Generative 3D Face Models

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Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generative process has lagged behind. If this new technology is to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Marek Kowalski , Stephan J. Garbin , Virginia Estellers , Tadas Baltrušaitis , Matthew Johnson , Jamie Shotton

Traditional 3D modeling requires technical expertise, specialized software, and time-intensive processes, making it inaccessible for many users. Our research aims to lower these barriers by combining generative AI and augmented reality (AR)…

Graphics · Computer Science 2025-05-01 Majid Behravan , Maryam Haghani , Denis Gracanin

Through a large-scale study over diverse face images, we show that facial attribute editing using modern generative AI models can severely degrade automated face recognition systems. This degradation persists even with identity-preserving…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Sudipta Banerjee , Sai Pranaswi Mullangi , Shruti Wagle , Chinmay Hegde , Nasir Memon

In this paper, we propose an effective face completion algorithm using a deep generative model. Different from well-studied background completion, the face completion task is more challenging as it often requires to generate semantically…

Computer Vision and Pattern Recognition · Computer Science 2017-04-20 Yijun Li , Sifei Liu , Jimei Yang , Ming-Hsuan Yang

Creating realistic 3D head assets for virtual characters that match a precise artistic vision remains labor-intensive. We present a novel framework that streamlines this process by providing artists with intuitive control over generated 3D…

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

In this paper, we investigate an open research task of generating 3D cartoon face shapes from single 2D GAN generated human faces and without 3D supervision, where we can also manipulate the facial expressions of the 3D shapes. To this end,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Hao Wang , Wenhao Shen , Guosheng Lin , Steven C. H. Hoi , Chunyan Miao

3D face reconstruction and face alignment are two fundamental and highly related topics in computer vision. Recently, some works start to use deep learning models to estimate the 3DMM coefficients to reconstruct 3D face geometry. However,…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Zihao Jian , Minshan Xie

Portrait editing is a popular subject in photo manipulation. The Generative Adversarial Network (GAN) advances the generating of realistic faces and allows more face editing. In this paper, we argue about three issues in existing…

Computer Vision and Pattern Recognition · Computer Science 2019-05-27 Shuyang Gu , Jianmin Bao , Hao Yang , Dong Chen , Fang Wen , Lu Yuan

Our goal is to create a realistic 3D facial avatar with hair and accessories using only a text description. While this challenge has attracted significant recent interest, existing methods either lack realism, produce unrealistic shapes, or…

Computer Vision and Pattern Recognition · Computer Science 2023-09-14 Hao Zhang , Yao Feng , Peter Kulits , Yandong Wen , Justus Thies , Michael J. Black

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

The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Alexander W. Bergman , Wang Yifan , Gordon Wetzstein

3D modeling has long been an important area in computer vision and computer graphics. Recently, thanks to the breakthroughs in neural representations and generative models, we witnessed a rapid development of 3D modeling. 3D human modeling,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Ruihe Wang , Yukang Cao , Kai Han , Kwan-Yee K. Wong

Recent advances in deep learning have significantly increased the performance of face recognition systems. The performance and reliability of these models depend heavily on the amount and quality of the training data. However, the…

Computer Vision and Pattern Recognition · Computer Science 2018-02-19 Adam Kortylewski , Andreas Schneider , Thomas Gerig , Bernhard Egger , Andreas Morel-Forster , Thomas Vetter

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

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

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

3D-aware portrait editing has a wide range of applications in multiple fields. However, current approaches are limited due that they can only perform mask-guided or text-based editing. Even by fusing the two procedures into a model, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Kangneng Zhou , Daiheng Gao , Xuan Wang , Jie Zhang , Peng Zhang , Xusen Sun , Longhao Zhang , Shiqi Yang , Bang Zhang , Liefeng Bo , Yaxing Wang , Ming-Ming Cheng

Image synthesis has witnessed substantial progress due to the increasing power of generative model. This paper we propose a novel generative approach for exemplar based facial editing in the form of the region inpainting. Our method first…

Computer Vision and Pattern Recognition · Computer Science 2020-06-02 Jingtao Guo , Yi Liu , Zhenzhen Qian , Zuowei Zhou

We present DreamBooth3D, an approach to personalize text-to-3D generative models from as few as 3-6 casually captured images of a subject. Our approach combines recent advances in personalizing text-to-image models (DreamBooth) with…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Amit Raj , Srinivas Kaza , Ben Poole , Michael Niemeyer , Nataniel Ruiz , Ben Mildenhall , Shiran Zada , Kfir Aberman , Michael Rubinstein , Jonathan Barron , Yuanzhen Li , Varun Jampani
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