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StyleGAN2 is a state-of-the-art network in generating realistic images. Besides, it was explicitly trained to have disentangled directions in latent space, which allows efficient image manipulation by varying latent factors. Editing…

Computer Vision and Pattern Recognition · Computer Science 2020-10-23 Yuri Viazovetskyi , Vladimir Ivashkin , Evgeny Kashin

This paper aims to bring fine-grained expression control while maintaining high-fidelity identity in portrait generation. This is challenging due to the mutual interference between expression and identity: (i) fine expression control…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Liangwei Jiang , Ruida Li , Zhifeng Zhang , Shuo Fang , Chenguang Ma

One-shot 3D talking portrait generation aims to reconstruct a 3D avatar from an unseen image, and then animate it with a reference video or audio to generate a talking portrait video. The existing methods fail to simultaneously achieve the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zhenhui Ye , Tianyun Zhong , Yi Ren , Jiaqi Yang , Weichuang Li , Jiawei Huang , Ziyue Jiang , Jinzheng He , Rongjie Huang , Jinglin Liu , Chen Zhang , Xiang Yin , Zejun Ma , Zhou Zhao

The StyleGAN family succeed in high-fidelity image generation and allow for flexible and plausible editing of generated images by manipulating the semantic-rich latent style space.However, projecting a real image into its latent space…

Computer Vision and Pattern Recognition · Computer Science 2023-02-01 Bingchuan Li , Tianxiang Ma , Peng Zhang , Miao Hua , Wei Liu , Qian He , Zili Yi

Recent studies have shown remarkable success in image-to-image translation for two domains. However, existing approaches have limited scalability and robustness in handling more than two domains, since different models should be built…

Computer Vision and Pattern Recognition · Computer Science 2018-09-24 Yunjey Choi , Minje Choi , Munyoung Kim , Jung-Woo Ha , Sunghun Kim , Jaegul Choo

Photo-realistic video portrait reenactment benefits virtual production and numerous VR/AR experiences. The task remains challenging as the reenacted expression should match the source while the lighting should be adjustable to new…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Youjia Wang , Taotao Zhou , Minzhang Li , Teng Xu , Minye Wu , Lan Xu , Jingyi Yu

Deep learning-based face recognition continues to face challenges due to its reliance on huge datasets obtained from web crawling, which can be costly to gather and raise significant real-world privacy concerns. To address this issue, we…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Minsoo Kim , Min-Cheol Sagong , Gi Pyo Nam , Junghyun Cho , Ig-Jae Kim

We propose a hybrid recurrent Video Colorization with Hybrid Generative Adversarial Network (VCGAN), an improved approach to video colorization using end-to-end learning. The VCGAN addresses two prevalent issues in the video colorization…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yuzhi Zhao , Lai-Man Po , Wing-Yin Yu , Yasar Abbas Ur Rehman , Mengyang Liu , Yujia Zhang , Weifeng Ou

In this paper, we explore a new domain for video-to-video translation. Motivated by the availability of animation movies that are adopted from illustrated books for children, we aim to stylize these videos with the style of the original…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Samet Hicsonmez , Nermin Samet , Fidan Samet , Oguz Bakir , Emre Akbas , Pinar Duygulu

A style mapper applies some fixed style to its input images (so, for example, taking faces to cartoons). This paper describes a simple procedure -- JoJoGAN -- to learn a style mapper from a single example of the style. JoJoGAN uses a GAN…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Min Jin Chong , David Forsyth

The introduction of high-quality image generation models, particularly the StyleGAN family, provides a powerful tool to synthesize and manipulate images. However, existing models are built upon high-quality (HQ) data as desired outputs,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-08 Dat Viet Thanh Nguyen , Phong Tran The , Tan M. Dinh , Cuong Pham , Anh Tuan Tran

Virtual try-on (VTON) has been widely explored for rendering garments onto person images, while its inverse task, virtual try-off (VTOFF), remains largely overlooked. VTOFF aims to recover standardized product images of garments directly…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Davide Lobba , Fulvio Sanguigni , Bin Ren , Marcella Cornia , Rita Cucchiara , Nicu Sebe

Free-form video inpainting is a very challenging task that could be widely used for video editing such as text removal. Existing patch-based methods could not handle non-repetitive structures such as faces, while directly applying…

Computer Vision and Pattern Recognition · Computer Science 2019-07-24 Ya-Liang Chang , Zhe Yu Liu , Kuan-Ying Lee , Winston Hsu

Recent advancements in personalized image generation using diffusion models have been noteworthy. However, existing methods suffer from inefficiencies due to the requirement for subject-specific fine-tuning. This computationally intensive…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Xu Peng , Junwei Zhu , Boyuan Jiang , Ying Tai , Donghao Luo , Jiangning Zhang , Wei Lin , Taisong Jin , Chengjie Wang , Rongrong Ji

Efficiently generating a freestyle 3D portrait with high quality and 3D-consistency is a promising yet challenging task. The portrait styles generated by most existing methods are usually restricted by their 3D generators, which are learned…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Tianxiang Ma , Kang Zhao , Jianxin Sun , Yingya Zhang , Jing Dong

Human-centric motion control in video generation remains a critical challenge, particularly when jointly controlling camera movements and human poses in scenarios like the iconic Grammy Glambot moment. While recent video diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Ruineng Li , Daitao Xing , Huiming Sun , Yuanzhou Ha , Jinglin Shen , Chiuman Ho

Advancement of machine learning techniques, combined with the availability of large-scale datasets, has significantly improved the accuracy and efficiency of facial recognition. Modern facial recognition systems are trained using large face…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Ajnas Muhammed , Iurri Medvedev , Nuno Gonçalves

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 like StyleGAN have promoted the growth of controllable facial editing. To address its core challenge of attribute decoupling in a single latent space, attempts have been made to adopt dual-space GAN for better…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Yanbo Xu , Yueqin Yin , Liming Jiang , Qianyi Wu , Chengyao Zheng , Chen Change Loy , Bo Dai , Wayne Wu

Photorealistic editing of portraits is a challenging task as humans are very sensitive to inconsistencies in faces. We present an approach for high-quality intuitive editing of the camera viewpoint and scene illumination in a portrait…

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