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Generative Adversarial Networks (GANs) have emerged as powerful tools for high-quality image generation and real image editing by manipulating their latent spaces. Recent advancements in GANs include 3D-aware models such as EG3D, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Bahri Batuhan Bilecen , Yigit Yalin , Ning Yu , Aysegul Dundar

Facial attribute editing aims to modify target attributes while preserving attribute-irrelevant content and overall image fidelity. Existing GAN-based methods provide favorable controllability, but often suffer from weak alignment between…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Wenmin Huang , Weiqi Luo , Xiaochun Cao , Jiwu Huang

Existing 3D-aware facial generation methods face a dilemma in quality versus editability: they either generate editable results in low resolution or high-quality ones with no editing flexibility. In this work, we propose a new approach that…

Computer Vision and Pattern Recognition · Computer Science 2022-06-01 Jingxiang Sun , Xuan Wang , Yichun Shi , Lizhen Wang , Jue Wang , Yebin Liu

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

GAN-based image editing task aims at manipulating image attributes in the latent space of generative models. Most of the previous 2D and 3D-aware approaches mainly focus on editing attributes in images with ambiguous semantics or regions…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Zhijun Zhai , Zengmao Wang , Xiaoxiao Long , Kaixuan Zhou , Bo Du

Recently, a surge of high-quality 3D-aware GANs have been proposed, which leverage the generative power of neural rendering. It is natural to associate 3D GANs with GAN inversion methods to project a real image into the generator's latent…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Fei Yin , Yong Zhang , Xuan Wang , Tengfei Wang , Xiaoyu Li , Yuan Gong , Yanbo Fan , Xiaodong Cun , Ying Shan , Cengiz Oztireli , Yujiu Yang

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

Facial Image inpainting aim is to restore the missing or corrupted regions in face images while preserving identity, structural consistency and photorealistic image quality, a task specifically created for photo restoration. Though there…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Abhigyan Bhattacharya , Hiranmoy Roy , Debotosh Bhattacharjee

Facial appearance editing is crucial for digital avatars, AR/VR, and personalized content creation, driving realistic user experiences. However, preserving identity with generative models is challenging, especially in scenarios with limited…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 MD Wahiduzzaman Khan , Mingshan Jia , Xiaolin Zhang , En Yu , Caifeng Shan , Kaska Musial-Gabrys

Identity preserving editing of faces is a generative task that enables modifying the illumination, adding/removing eyeglasses, face aging, editing hairstyles, modifying expression etc., while preserving the identity of the face. Recent…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Vishal Vinod

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

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

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

StyleGAN has achieved great progress in 2D face reconstruction and semantic editing via image inversion and latent editing. While studies over extending 2D StyleGAN to 3D faces have emerged, a corresponding generic 3D GAN inversion…

Computer Vision and Pattern Recognition · Computer Science 2022-12-19 Yushi Lan , Xuyi Meng , Shuai Yang , Chen Change Loy , Bo Dai

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

GAN inversion has been exploited in many face manipulation tasks, but 2D GANs often fail to generate multi-view 3D consistent images. The encoders designed for 2D GANs are not able to provide sufficient 3D information for the inversion and…

Computer Vision and Pattern Recognition · Computer Science 2023-02-21 Songlin Yang , Wei Wang , Bo Peng , Jing Dong

Previous portrait image generation methods roughly fall into two categories: 2D GANs and 3D-aware GANs. 2D GANs can generate high fidelity portraits but with low view consistency. 3D-aware GAN methods can maintain view consistency but their…

Computer Vision and Pattern Recognition · Computer Science 2022-03-22 Jingxiang Sun , Xuan Wang , Yong Zhang , Xiaoyu Li , Qi Zhang , Yebin Liu , Jue Wang

Latent space-based facial attribute editing methods have gained popularity in applications such as digital entertainment, virtual avatar creation, and human-computer interaction systems due to their potential for efficient and flexible…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Bo Liu , Xuan Cui , Run Zeng , Wei Duan , Chongwen Liu , Jinrui Qian , Lianggui Tang , Hongping Gan

Facial appearance plays an important role in our social lives. Subjective perception of women's beauty depends on various face-related (e.g., skin, shape, hair) and environmental (e.g., makeup, lighting, angle) factors. Similar to cosmetic…

Computer Vision and Pattern Recognition · Computer Science 2019-12-12 Xudong Liu , Ruizhe Wang , Chih-Fan Chen , Minglei Yin , Hao Peng , Shukhan Ng , Xin 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
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