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Diffusion Transformers (DiTs) excel at generation, but their global self-attention makes controllable, reference-image-based editing a distinct challenge. Unlike U-Nets, naively injecting local appearance into a DiT can disrupt its holistic…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Shengrong Gu , Ye Wang , Song Wu , Rui Ma , Qian Wang , Lanjun Wang , Zili Yi

Text-to-image (T2I) diffusion models have achieved remarkable success in generating high-quality images from textual prompts. However, their ability to store vast amounts of knowledge raises concerns in scenarios where selective forgetting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Gen Li , Yang Xiao , Jie Ji , Kaiyuan Deng , Bo Hui , Linke Guo , Xiaolong Ma

Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising process guided by text embeddings extracted from pretrained vision-language models such as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Seung Hyuk Lee , Songkuk Kim

The rise of text-to-image (T2I) models has increasingly raised concerns regarding the generation of risky content, such as sexual, violent, and copyright-protected images, highlighting the need for effective safeguards within the models…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Chenyu Zhang

Large-scale text-to-image (T2I) diffusion models have achieved remarkable generative performance about various concepts. With the limitation of privacy and safety in practice, the generative capability concerning NSFW (Not Safe For Work)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Jiahang Tu , Qian Feng , Jiahua Dong , Hanbin Zhao , Chao Zhang , Nicu Sebe , Hui Qian

Large-scale text-to-image generative models have shown remarkable ability to synthesize diverse and high-quality images. However, it is still challenging to directly apply these models for editing real images for two reasons. First, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Syed Muhmmad Israr , Feng Zhao

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

High-fidelity text-to-image diffusion models have revolutionized visual content generation, but their widespread use raises significant ethical concerns, including intellectual property protection and the misuse of synthetic media. To…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Yunzhuo Chen , Naveed Akhtar , Nur Al Hasan Haldar , Ajmal Mian

Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-generated image detection methods assume the availability of real/AI-generated images for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Sungik Choi , Hankook Lee , Jaehoon Lee , Seunghyun Kim , Stanley Jungkyu Choi , Moontae Lee

Text-to-image models encounter safety issues, including concerns related to copyright and Not-Safe-For-Work (NSFW) content. Despite several methods have been proposed for erasing inappropriate concepts from diffusion models, they often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Chao Gong , Kai Chen , Zhipeng Wei , Jingjing Chen , Yu-Gang Jiang

In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption. However, this progress has inadvertently opened avenues for potential misuse, particularly in generating inappropriate or…

Cryptography and Security · Computer Science 2024-04-02 Yijun Yang , Ruiyuan Gao , Xiaosen Wang , Tsung-Yi Ho , Nan Xu , Qiang Xu

Despite impressive recent advances in text-to-image diffusion models, obtaining high-quality images often requires prompt engineering by humans who have developed expertise in using them. In this work, we present NeuroPrompts, an adaptive…

Artificial Intelligence · Computer Science 2024-04-09 Shachar Rosenman , Vasudev Lal , Phillip Howard

While large-scale text-to-image diffusion models have demonstrated impressive image-generation capabilities, there are significant concerns about their potential misuse for generating unsafe content, violating copyright, and perpetuating…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Ruchika Chavhan , Da Li , Timothy Hospedales

Concept erasure in text-to-image diffusion models aims to disable pre-trained diffusion models from generating images related to a target concept. To perform reliable concept erasure, the properties of robustness and locality are desirable.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Chi-Pin Huang , Kai-Po Chang , Chung-Ting Tsai , Yung-Hsuan Lai , Fu-En Yang , Yu-Chiang Frank Wang

The widespread use of diffusion methods enables the creation of highly realistic images on demand, thereby posing significant risks to the integrity and safety of online information and highlighting the necessity of DeepFake detection. Our…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Di Yang , Yihao Huang , Qing Guo , Felix Juefei-Xu , Xiaojun Jia , Run Wang , Geguang Pu , Yang Liu

Recent text-to-image models have achieved impressive results in generating high-quality images. However, when tasked with multi-concept generation creating images that contain multiple characters or objects, existing methods often suffer…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Yang Zhang , Rui Zhang , Xuecheng Nie , Haochen Li , Jikun Chen , Yifan Hao , Xin Zhang , Luoqi Liu , Ling Li

Photographic style, as a composition of certain photographic concepts, is the charm behind renowned photographers. But learning and transferring photographic style need a profound understanding of how the photo is edited from the unknown…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Chengxuan Zhu , Shuchen Weng , Jiacong Fang , Peixuan Zhang , Si Li , Chao Xu , Boxin Shi

In the last two years, text-to-image diffusion models have become extremely popular. As their quality and usage increase, a major concern has been the need for better output control. In addition to prompt engineering, one effective method…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Clément Bonnet , Ariel N. Lee , Franck Wertel , Antoine Tamano , Tanguy Cizain , Pablo Ducru

Text-to-image (T2I) research has grown explosively in the past year, owing to the large-scale pre-trained diffusion models and many emerging personalization and editing approaches. Yet, one pain point persists: the text prompt engineering,…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Xingqian Xu , Jiayi Guo , Zhangyang Wang , Gao Huang , Irfan Essa , Humphrey Shi

Motivated by ethical and legal concerns, the scientific community is actively developing methods to limit the misuse of Text-to-Image diffusion models for reproducing copyrighted, violent, explicit, or personal information in the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Vitali Petsiuk , Kate Saenko
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