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Several research groups have shown that Generative Adversarial Networks (GANs) can generate photo-realistic images in recent years. Using the GANs, a map is created between a latent code and a photo-realistic image. This process can also be…

Computer Vision and Pattern Recognition · Computer Science 2022-03-22 Andrea Giardina , Soumya Subhra Paria , Adhikari Kaustubh

We propose LatentSwap, a simple face swapping framework generating a face swap latent code of a given generator. Utilizing randomly sampled latent codes, our framework is light and does not require datasets besides employing the pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Changho Choi , Minho Kim , Junhyeok Lee , Hyoung-Kyu Song , Younggeun Kim , Seungryong Kim

Drawing upon StyleGAN's expressivity and disentangled latent space, existing 2D approaches employ textual prompting to edit facial images with different attributes. In contrast, 3D-aware approaches that generate faces at different target…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Amandeep Kumar , Muhammad Awais , Sanath Narayan , Hisham Cholakkal , Salman Khan , Rao Muhammad Anwer

Face editing represents a popular research topic within the computer vision and image processing communities. While significant progress has been made recently in this area, existing solutions: (i) are still largely focused on…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Martin Pernuš , Vitomir Štruc , Simon Dobrišek

The classification of forged videos has been a challenge for the past few years. Deepfake classifiers can now reliably predict whether or not video frames have been tampered with. However, their performance is tied to both the dataset used…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Matthieu Delmas , Renaud Seguier

Manipulating facial expressions is a challenging task due to fine-grained shape changes produced by facial muscles and the lack of input-output pairs for supervised learning. Unlike previous methods using Generative Adversarial Networks…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Rumeysa Bodur , Binod Bhattarai , Tae-Kyun Kim

This paper presents an innovative approach to achieve face cartoonisation while preserving the original identity and accommodating various poses. Unlike previous methods in this field that relied on conditional-GANs, which posed challenges…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Kushal Jain , Ankith Varun J , Anoop Namboodiri

Face aging, which aims at aesthetically rendering a given face to predict its future appearance, has received significant research attention in recent years. Although great progress has been achieved with the success of Generative…

Computer Vision and Pattern Recognition · Computer Science 2019-11-18 Yunfan Liu , Qi Li , Zhenan Sun , Tieniu Tan

In this research work, we proposed a novel ChildGAN, a pair of GAN networks for generating synthetic boys and girls facial data derived from StyleGAN2. ChildGAN is built by performing smooth domain transfer using transfer learning. It…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Muhammad Ali Farooq , Wang Yao , Gabriel Costache , Peter Corcoran

Taking full advantage of the excellent performance of StyleGAN, style transfer-based face swapping methods have been extensively investigated recently. However, these studies require separate face segmentation and blending modules for…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Chenhao Lin , Pengbin Hu , Chao Shen , Qian Li

Despite recent advances in semantic manipulation using StyleGAN, semantic editing of real faces remains challenging. The gap between the $W$ space and the $W$+ space demands an undesirable trade-off between reconstruction quality and…

Computer Vision and Pattern Recognition · Computer Science 2022-07-22 Heyi Li , Jinlong Liu , Xinyu Zhang , Yunzhi Bai , Huayan Wang , Klaus Mueller

Advances in face rotation, along with other face-based generative tasks, are more frequent as we advance further in topics of deep learning. Even as impressive milestones are achieved in synthesizing faces, the importance of preserving…

Computer Vision and Pattern Recognition · Computer Science 2020-12-09 Yu Yin , Joseph P. Robinson , Songyao Jiang , Yue Bai , Can Qin , Yun Fu

The recent advancements in image-text diffusion models have stimulated research interest in large-scale 3D generative models. Nevertheless, the limited availability of diverse 3D resources presents significant challenges to learning. In…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Chi Zhang , Yiwen Chen , Yijun Fu , Zhenglin Zhou , Gang YU , Billzb Wang , Bin Fu , Tao Chen , Guosheng Lin , Chunhua Shen

Face reenactment methods attempt to restore and re-animate portrait videos as realistically as possible. Existing methods face a dilemma in quality versus controllability: 2D GAN-based methods achieve higher image quality but suffer in…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Lizhen Wang , Xiaochen Zhao , Jingxiang Sun , Yuxiang Zhang , Hongwen Zhang , Tao Yu , Yebin Liu

Although significant progress has been made in synthesizing high-quality and visually realistic face images by unconditional Generative Adversarial Networks (GANs), there still lacks of control over the generation process in order to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-23 Xianxu Hou , Xiaokang Zhang , Linlin Shen , Zhihui Lai , Jun Wan

A lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In the recent works, the texture features either correspond to…

Computer Vision and Pattern Recognition · Computer Science 2022-03-28 Baris Gecer , Stylianos Ploumpis , Irene Kotsia , Stefanos Zafeiriou

There are five features to consider when using generative adversarial networks to apply makeup to photos of the human face. These features include (1) facial components, (2) interactive color adjustments, (3) makeup variations, (4)…

Computer Vision and Pattern Recognition · Computer Science 2020-09-25 Daichi Horita , Kiyoharu Aizawa

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

Face verification has come into increasing focus in various applications including the European Entry/Exit System, which integrates face recognition mechanisms. At the same time, the rapid advancement of biometric authentication requires…

Computer Vision and Pattern Recognition · Computer Science 2021-04-08 Haoyu Zhang , Marcel Grimmer , Raghavendra Ramachandra , Kiran Raja , Christoph Busch

Recent works on language-guided image manipulation have shown great power of language in providing rich semantics, especially for face images. However, the other natural information, motions, in language is less explored. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Tiankai Hang , Huan Yang , Bei Liu , Jianlong Fu , Xin Geng , Baining Guo