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Related papers: Disciplined Diffusion: Text-to-Image Diffusion Mod…

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In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images.They either finetune the model, or invert the image in the latent space of the pretrained model. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Although diffusion-based techniques have shown remarkable success in image generation and editing tasks, their abuse can lead to severe negative social impacts. Recently, some works have been proposed to provide defense against the abuse of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Zheng Li , Liangbin Xie , Jiantao Zhou , Xintao Wang , Haiwei Wu , Jinyu Tian

Image editing aims to edit the given synthetic or real image to meet the specific requirements from users. It is widely studied in recent years as a promising and challenging field of Artificial Intelligence Generative Content (AIGC).…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Xincheng Shuai , Henghui Ding , Xingjun Ma , Rongcheng Tu , Yu-Gang Jiang , Dacheng Tao

Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, these models present notable safety concerns, including the risk of generating harmful,…

Computation and Language · Computer Science 2025-07-28 Lijun Li , Zhelun Shi , Xuhao Hu , Bowen Dong , Yiran Qin , Xihui Liu , Lu Sheng , Jing Shao

Text-to-image diffusion models have achieved remarkable success in generating high-quality contents from text prompts. However, their reliance on publicly available data and the growing trend of data sharing for fine-tuning make these…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Sangwon Jang , June Suk Choi , Jaehyeong Jo , Kimin Lee , Sung Ju Hwang

The generative AI revolution in recent years has been spurred by an expansion in compute power and data quantity, which together enable extensive pre-training of powerful text-to-image (T2I) models. With their greater capabilities to…

The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Text-to-image models have shown remarkable capabilities in generating high-quality images from natural language descriptions. However, these models are highly vulnerable to adversarial prompts, which can bypass safety measures and produce…

Cryptography and Security · Computer Science 2025-10-16 Peigui Qi , Kunsheng Tang , Wenbo Zhou , Weiming Zhang , Nenghai Yu , Tianwei Zhang , Qing Guo , Jie Zhang

Diffusion models have demonstrated remarkable capability in generating high-quality visual content from textual descriptions. However, since these models are trained on large-scale internet data, they inevitably learn undesirable concepts,…

Machine Learning · Computer Science 2025-02-18 Anh Bui , Khanh Doan , Trung Le , Paul Montague , Tamas Abraham , Dinh Phung

The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Yichen Sun , Zhixuan Chu , Zhan Qin , Kui Ren

Recent advances in text-to-image diffusion models have enabled the generation of diverse and high-quality images. While impressive, the images often fall short of depicting subtle details and are susceptible to errors due to ambiguity in…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Idan Schwartz , Vésteinn Snæbjarnarson , Hila Chefer , Ryan Cotterell , Serge Belongie , Lior Wolf , Sagie Benaim

Text-to-image (T2I) models have been widely applied in generating high-fidelity images across various domains. However, these models may also be abused to produce Not-Safe-for-Work (NSFW) content via jailbreak attacks. Existing jailbreak…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Xingkai Peng , Jun Jiang , Meng Tong , Shuai Li , Weiming Zhang , Nenghai Yu , Kejiang Chen

Text-to-image (T2I) models have emerged as a significant advancement in generative AI; however, there exist safety concerns regarding their potential to produce harmful image outputs even when users input seemingly safe prompts. This…

Computers and Society · Computer Science 2024-08-19 Susan Hao , Renee Shelby , Yuchi Liu , Hansa Srinivasan , Mukul Bhutani , Burcu Karagol Ayan , Ryan Poplin , Shivani Poddar , Sarah Laszlo

Recent text-to-image diffusion models have shown surprising performance in generating high-quality images. However, concerns have arisen regarding the unauthorized data usage during the training or fine-tuning process. One example is when a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Zhenting Wang , Chen Chen , Lingjuan Lyu , Dimitris N. Metaxas , Shiqing Ma

Text-to-Image (T2I) models have shown great performance in generating images based on textual prompts. However, these models are vulnerable to unsafe input to generate unsafe content like sexual, harassment and illegal-activity images.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Zongyu Wu , Hongcheng Gao , Yueze Wang , Xiang Zhang , Suhang Wang

Text-to-image diffusion models have emerged as powerful tools for high-quality image generation and editing. Many existing approaches rely on text prompts as editing guidance. However, these methods are constrained by the need for manual…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Yuanyuan Chang , Yinghua Yao , Tao Qin , Mengmeng Wang , Ivor Tsang , Guang Dai

Text-to-image (T2I) models have raised increasing safety concerns due to their capacity to generate NSFW and other banned objects. To mitigate these risks, safety filters and concept removal techniques have been introduced to block…

Cryptography and Security · Computer Science 2026-01-13 Xi Ye , Yiwen Liu , Lina Wang , Run Wang , Geying Yang , Yufei Hou , Jiayi Yu

This paper addresses the societal concerns arising from large-scale text-to-image diffusion models for generating potentially harmful or copyrighted content. Existing models rely heavily on internet-crawled data, wherein problematic…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Sanghyun Kim , Seohyeon Jung , Balhae Kim , Moonseok Choi , Jinwoo Shin , Juho Lee

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
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