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Artistic styles are defined by both their structural and appearance elements. Existing neural stylization techniques primarily focus on transferring appearance-level features such as color and texture, often neglecting the equally crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Ruixiang Jiang , Changwen Chen

Diffusion models have proven to be highly effective in generating high-quality images. However, adapting large pre-trained diffusion models to new domains remains an open challenge, which is critical for real-world applications. This paper…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Enze Xie , Lewei Yao , Han Shi , Zhili Liu , Daquan Zhou , Zhaoqiang Liu , Jiawei Li , Zhenguo Li

Diffusion-based text-to-image generation models have significantly advanced the field of art content synthesis. However, current portrait stylization methods generally require either model fine-tuning based on examples or the employment of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Jin Liu , Huaibo Huang , Jie Cao , Ran He

While diffusion-based methods have shown impressive capabilities in capturing diverse and complex hairstyles, their ability to generate consistent and high-quality multi-view outputs -- crucial for real-world applications such as digital…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Kuiyuan Sun , Yuxuan Zhang , Jichao Zhang , Jiaming Liu , Wei Wang , Niculae Sebe , Yao Zhao

Unveiling the real appearance of retouched faces to prevent malicious users from deceptive advertising and economic fraud has been an increasing concern in the era of digital economics. This article makes the first attempt to investigate…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Fengchuang Xing , Xiaowen Shi , Yuan-Gen Wang , Chunsheng Yang

We present StyleClone, a method for training image-to-image translation networks to stylize faces in a specific style, even with limited style images. Our approach leverages textual inversion and diffusion-based guided image generation to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Neeraj Matiyali , Siddharth Srivastava , Gaurav Sharma

Modern learning-based approaches to 3D-aware image synthesis achieve high photorealism and 3D-consistent viewpoint changes for the generated images. Existing approaches represent instances in a shared canonical space. However, for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Katja Schwarz , Seung Wook Kim , Jun Gao , Sanja Fidler , Andreas Geiger , Karsten Kreis

We introduce FabricDiffusion, a method for transferring fabric textures from a single clothing image to 3D garments of arbitrary shapes. Existing approaches typically synthesize textures on the garment surface through 2D-to-3D texture…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Cheng Zhang , Yuanhao Wang , Francisco Vicente Carrasco , Chenglei Wu , Jinlong Yang , Thabo Beeler , Fernando De la Torre

Recent advancements in image synthesis are fueled by the advent of large-scale diffusion models. Yet, integrating realistic object visualizations seamlessly into new or existing backgrounds without extensive training remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Phillip Mueller , Jannik Wiese , Ioan Craciun , Lars Mikelsons

Recent guidance methods in diffusion models steer reverse sampling by perturbing the model to construct an implicit weak model and guide generation away from it. Among these approaches, attention perturbation has demonstrated strong…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Donghoon Ahn , Jiwon Kang , Sanghyun Lee , Minjae Kim , Jaewon Min , Wooseok Jang , Sangwu Lee , Sayak Paul , Susung Hong , Seungryong Kim

Text-to-image diffusion models have revolutionized image synthesis and editing, but precise control over stylistic attributes remains a challenge, often causing unintended content modifications. We propose an approach for fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Max Reimann , Benito Buchheim , Jürgen Döllner

Similar to facial beautification in real life, 3D virtual avatars require personalized customization to enhance their visual appeal, yet this area remains insufficiently explored. Although current 3D Gaussian editing methods can be adapted…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Yiming Zhong , Xiaolin Zhang , Ligang Liu , Yao Zhao , Yunchao Wei

Image generation in the fashion domain has predominantly focused on preserving body characteristics or following input prompts, but little attention has been paid to improving the inherent fashionability of the output images. This paper…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Qice Qin , Yuki Hirakawa , Ryotaro Shimizu , Takuya Furusawa , Edgar Simo-Serra

The rapid development of generative diffusion models has significantly advanced the field of style transfer. However, most current style transfer methods based on diffusion models typically involve a slow iterative optimization process,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Feihong He , Gang Li , Fuhui Sun , Mengyuan Zhang , Lingyu Si , Xiaoyan Wang , Li Shen

Diffusion models can synthesize realistic co-speech video from audio for various applications, such as video creation and virtual agents. However, existing diffusion-based methods are slow due to numerous denoising steps and costly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Beijia Lu , Ziyi Chen , Jing Xiao , Jun-Yan Zhu

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

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

Human body restoration plays a vital role in various applications related to the human body. Despite recent advances in general image restoration using generative models, their performance in human body restoration remains mediocre, often…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Yiming Zhang , Zhe Wang , Xinjie Li , Yunchen Yuan , Chengsong Zhang , Xiao Sun , Zhihang Zhong , Jian Wang

Generating high-quality and person-generic visual dubbing remains a challenge. Recent innovation has seen the advent of a two-stage paradigm, decoupling the rendering and lip synchronization process facilitated by intermediate…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Tao Liu , Chenpeng Du , Shuai Fan , Feilong Chen , Kai Yu

Pose and body shape editing in a human image has received increasing attention. However, current methods often struggle with dataset biases and deteriorate realism and the person's identity when users make large edits. We propose a one-shot…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Yuta Okuyama , Yuki Endo , Yoshihiro Kanamori
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