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Related papers: Edit One for All: Interactive Batch Image Editing

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A precise and user-friendly manipulation of image content while preserving image fidelity has always been crucial to the field of image editing. Thanks to the power of generative models, recent point-based image editing methods allow users…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Minxing Luo , Wentao Cheng , Jian Yang

While GANs can produce photo-realistic images in ideal conditions for certain domains, the generation of full-body human images remains difficult due to the diversity of identities, hairstyles, clothing, and the variance in pose. Instead of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-15 Anna Frühstück , Krishna Kumar Singh , Eli Shechtman , Niloy J. Mitra , Peter Wonka , Jingwan Lu

StyleGAN generates photorealistic portrait images of faces with eyes, teeth, hair and context (neck, shoulders, background), but lacks a rig-like control over semantic face parameters that are interpretable in 3D, such as face pose,…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Ayush Tewari , Mohamed Elgharib , Gaurav Bharaj , Florian Bernard , Hans-Peter Seidel , Patrick Pérez , Michael Zollhöfer , Christian Theobalt

Instruction-guided 3D editing is a rapidly emerging field with the potential to broaden access to 3D content creation. However, existing methods face critical limitations: optimization-based approaches are prohibitively slow, while…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Weiwei Cai , Shuangkang Fang , Weicai Ye , Xin Dong , Yunhan Yang , Xuanyang Zhang , Wei Cheng , Yanpei Cao , Gang Yu , Tao Chen

Digital face manipulation has become a popular and fascinating way to touch images with the prevalence of smartphones and social networks. With a wide variety of user preferences, facial expressions, and accessories, a general and flexible…

Computer Vision and Pattern Recognition · Computer Science 2018-04-02 Ying-Cong Chen , Huaijia Lin , Michelle Shu , Ruiyu Li , Xin Tao , Yangang Ye , Xiaoyong Shen , Jiaya Jia

In this paper, we propose an approach to obtain a personalized generative prior with explicit control over a set of attributes. We build upon MyStyle, a recently introduced method, that tunes the weights of a pre-trained StyleGAN face…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Libing Zeng , Lele Chen , Yi Xu , Nima Kalantari

Previous methods have dealt with discrete manipulation of facial attributes such as smile, sad, angry, surprise etc, out of canonical expressions and they are not scalable, operating in single modality. In this paper, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2020-10-07 Jiali Duan , Xiaoyuan Guo , Yuhang Song , Chao Yang , C. -C. Jay Kuo

Instruction-guided image editing consists in taking an image and an instruction and deliverring that image altered according to that instruction. State-of-the-art approaches to this task suffer from the typical scaling up and domain…

Computation and Language · Computer Science 2025-03-05 Rodrigo Santos , António Branco , João Silva , João Rodrigues

Face editing methods, essential for tasks like virtual avatars, digital human synthesis and identity preservation, have traditionally been built upon GAN-based techniques, while recent focus has shifted to diffusion-based models due to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Mengting Wei , Tuomas Varanka , Yante Li , Xingxun Jiang , Huai-Qian Khor , Guoying Zhao

Recent advances in face manipulation using StyleGAN have produced impressive results. However, StyleGAN is inherently limited to cropped aligned faces at a fixed image resolution it is pre-trained on. In this paper, we propose a simple and…

Computer Vision and Pattern Recognition · Computer Science 2023-07-24 Shuai Yang , Liming Jiang , Ziwei Liu , Chen Change Loy

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

The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quality remains an open problem. In this study, we revisit…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Kai Katsumata , Duc Minh Vo , Bei Liu , Hideki Nakayama

For the last decades, the concern of producing convincing facial animation has garnered great interest, that has only been accelerating with the recent explosion of 3D content in both entertainment and professional activities. The use of…

Graphics · Computer Science 2020-10-13 Eloïse Berson , Catherine Soladié , Nicolas Stoiber

3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images in the multi-object scenario still remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Qian Wang , Yiqun Wang , Michael Birsak , Peter Wonka

Group portrait editing is highly desirable since users constantly want to add a person, delete a person, or manipulate existing persons. It is also challenging due to the intricate dynamics of human interactions and the diverse gestures. In…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Yuming Jiang , Nanxuan Zhao , Qing Liu , Krishna Kumar Singh , Shuai Yang , Chen Change Loy , Ziwei Liu

Traditional point-based image editing methods rely on iterative latent optimization or geometric transformations, which are either inefficient in their processing or fail to capture the semantic relationships within the image. These methods…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Biao Yang , Muqi Huang , Yuhui Zhang , Yun Xiong , Kun Zhou , Xi Chen , Shiyang Zhou , Huishuai Bao , Chuan Li , Feng Shi , Hualei Liu

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

Face image manipulation via three-dimensional guidance has been widely applied in various interactive scenarios due to its semantically-meaningful understanding and user-friendly controllability. However, existing 3D-morphable-model-based…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Can Wang , Menglei Chai , Mingming He , Dongdong Chen , Jing Liao

Recent advances in generative adversarial networks (GANs) have led to remarkable achievements in face image synthesis. While methods that use style-based GANs can generate strikingly photorealistic face images, it is often difficult to…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Safa C. Medin , Bernhard Egger , Anoop Cherian , Ye Wang , Joshua B. Tenenbaum , Xiaoming Liu , Tim K. Marks

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