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While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a significant challenge due to the complexities of multi-view consistency and spatial control.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jinxin Ai , Matthias Nießner , Ziya Erkoç

Image rendering from line drawings is vital in design and image generation technologies reduce costs, yet professional line drawings demand preserving complex details. Text prompts struggle with accuracy, and image translation struggles…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xi Wang , Hongzhen Li , Heng Fang , Yichen Peng , Haoran Xie , Xi Yang , Chuntao Li

Artistic style transfer aims to transfer the learned style onto an arbitrary content image. However, most existing style transfer methods can only render consistent artistic stylized images, making it difficult for users to get enough…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhanjie Zhang , Quanwei Zhang , Guangyuan Li , Junsheng Luan , Mengyuan Yang , Yun Wang , Lei Zhao

Recent advances in diffusion generative models have yielded remarkable progress. While the quality of generated content continues to improve, these models have grown considerably in size and complexity. This increasing computational burden…

Machine Learning · Computer Science 2025-03-13 Reza Shirkavand , Peiran Yu , Shangqian Gao , Gowthami Somepalli , Tom Goldstein , Heng Huang

Recent advancements in diffusion models have made generative image editing more accessible, enabling creative edits but raising ethical concerns, particularly regarding malicious edits to human portraits that threaten privacy and identity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Hanhui Wang , Yihua Zhang , Ruizheng Bai , Yue Zhao , Sijia Liu , Zhengzhong Tu

Fine-tuning advanced diffusion models for high-quality image stylization usually requires large training datasets and substantial computational resources, hindering their practical applicability. We propose Ada-Adapter, a novel framework…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Jia Liu , Changlin Li , Qirui Sun , Jiahui Ming , Chen Fang , Jue Wang , Bing Zeng , Shuaicheng Liu

In practical application, the widespread deployment of diffusion models often necessitates substantial investment in training. As diffusion models find increasingly diverse applications, concerns about potential misuse highlight the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Jijia Yang , Sen Peng , Xiaohua Jia

Web-based AI image generation has become an innovative art form that can generate novel artworks with the rapid development of the diffusion model. However, this new technique brings potential copyright infringement risks as it may…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Junlei Zhou , Jiashi Gao , Ziwei Wang , Xuetao Wei

Watermarking has become one of promising techniques to not only aid in identifying AI-generated images but also serve as a deterrent against the unethical use of these models. However, the robustness of watermarking techniques has not been…

Cryptography and Security · Computer Science 2024-11-05 Xiaodong Wu , Xiangman Li , Jianbing Ni

In the context of flexible manufacturing systems that are required to produce different types and quantities of products with minimal reconfiguration, this paper addresses the problem of unsupervised multi-class anomaly detection: develop a…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Haonan Yin , Guanlong Jiao , Qianhui Wu , Borje F. Karlsson , Biqing Huang , Chin Yew Lin

Recently, diffusion models have emerged as promising newcomers in the field of generative models, shining brightly in image generation. However, when employed for object removal tasks, they still encounter issues such as generating random…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Wenhao Sun , Benlei Cui , Xue-Mei Dong , Jingqun Tang

In this paper, we make the first attempt to align diffusion models for image inpainting with human aesthetic standards via a reinforcement learning framework, significantly improving the quality and visual appeal of inpainted images.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Kendong Liu , Zhiyu Zhu , Chuanhao Li , Hui Liu , Huanqiang Zeng , Junhui Hou

Style transfer is an inventive process designed to create an image that maintains the essence of the original while embracing the visual style of another. Although diffusion models have demonstrated impressive generative power in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Haofan Wang , Peng Xing , Renyuan Huang , Hao Ai , Qixun Wang , Xu Bai

In recent years, diffusion models have achieved remarkable success in the realm of high-quality image generation, garnering increased attention. This surge in interest is paralleled by a growing concern over the security threats associated…

Machine Learning · Computer Science 2024-06-04 Sen Li , Junchi Ma , Minhao Cheng

Recent powerful vision classifiers are biased towards textures, while shape information is overlooked by the models. A simple attempt by augmenting training images using the artistic style transfer method, called Stylized ImageNet, can…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Sanghyuk Chun , Song Park

Text-to-image diffusion models, such as Stable Diffusion, have shown exceptional potential in generating high-quality images. However, recent studies highlight concerns over the use of unauthorized data in training these models, which may…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Soumil Datta , Shih-Chieh Dai , Leo Yu , Guanhong Tao

Cultural heritage applications and advanced machine learning models are creating a fruitful synergy to provide effective and accessible ways of interacting with artworks. Smart audio-guides, personalized art-related content and gamification…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Dario Cioni , Lorenzo Berlincioni , Federico Becattini , Alberto del Bimbo

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts. However, controlling these models to ensure consistent style remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Amir Hertz , Andrey Voynov , Shlomi Fruchter , Daniel Cohen-Or

Structural information in images is crucial for aesthetic assessment, and it is widely recognized in the artistic field that imitating the structure of other works significantly infringes on creators' rights. The advancement of diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Chuanwei Huang , Zexi Jia , Hongyan Fei , Yeshuang Zhu , Zhiqiang Yuan , Jinchao Zhang , Jie Zhou