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Related papers: Controllable Face Aging

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Generative models have been widely studied in computer vision. Recently, diffusion models have drawn substantial attention due to the high quality of their generated images. A key desired property of image generative models is the ability…

Computer Vision and Pattern Recognition · Computer Science 2022-12-20 Qiucheng Wu , Yujian Liu , Handong Zhao , Ajinkya Kale , Trung Bui , Tong Yu , Zhe Lin , Yang Zhang , Shiyu Chang

The appearances of children are inherited from their parents, which makes it feasible to predict them. Predicting realistic children's faces may help settle many social problems, such as age-invariant face recognition, kinship verification,…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Yuzhi Zhao , Lai-Man Po , Xuehui Wang , Qiong Yan , Wei Shen , Yujia Zhang , Wei Liu , Chun-Kit Wong , Chiu-Sing Pang , Weifeng Ou , Wing-Yin Yu , Buhua Liu

Facial aging and facial rejuvenation analyze a given face photograph to predict a future look or estimate a past look of the person. To achieve this, it is critical to preserve human identity and the corresponding aging progression and…

Computer Vision and Pattern Recognition · Computer Science 2018-04-10 Haiping Zhu , Qi Zhou , Junping Zhang , James Z. Wang

Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech. This is a challenging task because face appearance variation and semantics of speech are coupled together in the subtle movements of…

Computer Vision and Pattern Recognition · Computer Science 2019-04-24 Hang Zhou , Yu Liu , Ziwei Liu , Ping Luo , Xiaogang Wang

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue by using…

Computer Vision and Pattern Recognition · Computer Science 2016-05-04 Hongyu Yang , Di Huang , Yunhong Wang , Heng Wang , Yuanyan Tang

Face aging techniques have used generative adversarial networks (GANs) and style transfer learning to transform one's appearance to look younger/older. Identity is maintained by conditioning these generative networks on a learned vector…

Sound · Computer Science 2021-10-07 Justin Wilson , Sunyeong Park , Seunghye J. Wilson , Ming C. Lin

Generating and manipulating human facial images using high-level attributal controls are important and interesting problems. The models proposed in previous work can solve one of these two problems (generation or manipulation), but not both…

Computer Vision and Pattern Recognition · Computer Science 2017-04-10 Weidong Yin , Yanwei Fu , Leonid Sigal , Xiangyang Xue

Generative adversarial networks have been widely used in image synthesis in recent years and the quality of the generated image has been greatly improved. However, the flexibility to control and decouple facial attributes (e.g., eyes, nose,…

Computer Vision and Pattern Recognition · Computer Science 2021-08-26 Xiao Cui , Wengang Zhou , Yang Hu , Weilun Wang , Houqiang Li

Despite the recent advance of Generative Adversarial Networks (GANs) in high-fidelity image synthesis, there lacks enough understanding of how GANs are able to map a latent code sampled from a random distribution to a photo-realistic image.…

Computer Vision and Pattern Recognition · Computer Science 2020-04-01 Yujun Shen , Jinjin Gu , Xiaoou Tang , Bolei Zhou

Attribute guided face image synthesis aims to manipulate attributes on a face image. Most existing methods for image-to-image translation can either perform a fixed translation between any two image domains using a single attribute or…

Computer Vision and Pattern Recognition · Computer Science 2019-05-02 Behzad Bozorgtabar , Mohammad Saeed Rad , Hazım Kemal Ekenel , Jean-Philippe Thiran

In this paper, we address the problem of face aging: generating past or future facial images by incorporating age-related changes to the given face. Previous aging methods rely solely on human facial image datasets and are thus constrained…

Computer Vision and Pattern Recognition · Computer Science 2023-09-21 Xiangyi Chen , Stéphane Lathuilière

Attribute control in generative tasks aims to modify personal attributes, such as age and gender while preserving the identity information in the source sample. Although significant progress has been made in controlling facial attributes in…

Sound · Computer Science 2025-01-06 Xuyuan Li , Zengqiang Shang. Li Wang , Pengyuan Zhang

The great advancements of generative adversarial networks and face recognition models in computer vision have made it possible to swap identities on images from single sources. Although a lot of studies seems to have proposed almost…

Computer Vision and Pattern Recognition · Computer Science 2023-07-21 Kaede Shiohara , Xingchao Yang , Takafumi Taketomi

In this paper, we aim to automatically render aging faces in a personalized way. Basically, a set of age-group specific dictionaries are learned, where the dictionary bases corresponding to the same index yet from different dictionaries…

Computer Vision and Pattern Recognition · Computer Science 2015-10-23 Xiangbo Shu , Jinhui Tang , Hanjiang Lai , Luoqi Liu , Shuicheng Yan

"If I provide you a face image of mine (without telling you the actual age when I took the picture) and a large amount of face images that I crawled (containing labeled faces of different ages but not necessarily paired), can you show me…

Computer Vision and Pattern Recognition · Computer Science 2017-03-30 Zhifei Zhang , Yang Song , Hairong Qi

We present a deep learning approach for high resolution face completion with multiple controllable attributes (e.g., male and smiling) under arbitrary masks. Face completion entails understanding both structural meaningfulness and…

Computer Vision and Pattern Recognition · Computer Science 2018-01-24 Zeyuan Chen , Shaoliang Nie , Tianfu Wu , Christopher G. Healey

Generating novel, yet realistic, images of persons is a challenging task due to the complex interplay between the different image factors, such as the foreground, background and pose information. In this work, we aim at generating such…

Computer Vision and Pattern Recognition · Computer Science 2018-06-18 Liqian Ma , Qianru Sun , Stamatios Georgoulis , Luc Van Gool , Bernt Schiele , Mario Fritz

Prior knowledge of face shape and structure plays an important role in face inpainting. However, traditional face inpainting methods mainly focus on the generated image resolution of the missing portion without consideration of the special…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Xian Zhang , Xin Wang , Bin Kong , Canghong Shi , Youbing Yin , Qi Song , Siwei Lyu , Jiancheng Lv , Canghong Shi , Xiaojie Li

Face aging, which renders aging faces for an input face, has attracted extensive attention in the multimedia research. Recently, several conditional Generative Adversarial Nets (GANs) based methods have achieved great success. They can…

Computer Vision and Pattern Recognition · Computer Science 2018-02-02 Si Liu , Yao Sun , Defa Zhu , Renda Bao , Wei Wang , Xiangbo Shu , Shuicheng Yan

Recent advances in facial landmark detection achieve success by learning discriminative features from rich deformation of face shapes and poses. Besides the variance of faces themselves, the intrinsic variance of image styles, e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2018-03-23 Xuanyi Dong , Yan Yan , Wanli Ouyang , Yi Yang