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Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

Text-to-image diffusion models can generate diverse content with flexible prompts, which makes them well-suited for customization through fine-tuning with a small amount of user-provided data. However, controllable fine-tuning that prevents…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Ziyao Zeng , Jingcheng Ni , Ruyi Liu , Alex Wong

Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can generate offensive or disturbing imagery when provided with harmful inputs. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chi Zhang , Changjia Zhu , Xiaowen Li , Yao Liu , Zhuo Lu

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

The success of recent text-to-image diffusion models is largely due to their capacity to be guided by a complex text prompt, which enables users to precisely describe the desired content. However, these models struggle to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang

Text-conditioned diffusion models can generate impressive images, but fall short when it comes to fine-grained control. Unlike direct-editing tools like Photoshop, text conditioned models require the artist to perform "prompt engineering,"…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Michelle Shu , Charles Herrmann , Richard Strong Bowen , Forrester Cole , Ramin Zabih

Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. Recent research has extended these models to support text-guided image editing. While text guidance is an intuitive editing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jooyoung Choi , Yunjey Choi , Yunji Kim , Junho Kim , Sungroh Yoon

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

Social media platforms struggle to protect users from harmful content through content moderation. These platforms have recently leveraged machine learning models to cope with the vast amount of user-generated content daily. Since moderation…

Machine Learning · Computer Science 2023-01-27 Donghyun Son , Byounggyu Lew , Kwanghee Choi , Yongsu Baek , Seungwoo Choi , Beomjun Shin , Sungjoo Ha , Buru Chang

Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized modifications. To address this, we propose SecureT2I, a…

Cryptography and Security · Computer Science 2025-07-08 Xiaodong Wu , Xiangman Li , Qi Li , Jianbing Ni , Rongxing Lu

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

The quality of the prompts provided to text-to-image diffusion models determines how faithful the generated content is to the user's intent, often requiring `prompt engineering'. To harness visual concepts from target images without prompt…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Shweta Mahajan , Tanzila Rahman , Kwang Moo Yi , Leonid Sigal

In text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results. However, these models encounter challenges when processing text prompts containing multiple entities and attributes.…

Computation and Language · Computer Science 2024-04-23 Yihang Wu , Xiao Cao , Kaixin Li , Zitan Chen , Haonan Wang , Lei Meng , Zhiyong Huang

There is an ongoing debate about how to moderate toxic speech on social media and the impact of content moderation on online discourse. This paper proposes and validates a methodology for measuring the content-moderation-induced distortions…

Social and Information Networks · Computer Science 2026-03-04 Mahyar Habibi , Dirk Hovy , Carlo Schwarz

Text-to-image diffusion models often make implicit assumptions about the world when generating images. While some assumptions are useful (e.g., the sky is blue), they can also be outdated, incorrect, or reflective of social biases present…

Computer Vision and Pattern Recognition · Computer Science 2023-08-28 Hadas Orgad , Bahjat Kawar , Yonatan Belinkov

Content moderation plays a critical role in shaping safe and inclusive online environments, balancing platform standards, user expectations, and regulatory frameworks. Traditionally, this process involves operationalising policies into…

The recent large-scale generative modeling has attained unprecedented performance especially in producing high-fidelity images driven by text prompts. Text inversion (TI), alongside the text-to-image model backbones, is proposed as an…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Jianan Yang , Haobo Wang , Yanming Zhang , Ruixuan Xiao , Sai Wu , Gang Chen , Junbo Zhao

Recent advancements in Text-to-Image (T2I) diffusion models have demonstrated impressive success in generating high-quality images with zero-shot generalization capabilities. Yet, current models struggle to closely adhere to prompt…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Hyun Kang , Dohae Lee , Myungjin Shin , In-Kwon Lee

Text-to-image (TTI) diffusion models have demonstrated impressive results in generating high-resolution images of complex and imaginative scenes. Recent approaches have further extended these methods with personalization techniques that…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Tanzila Rahman , Shweta Mahajan , Hsin-Ying Lee , Jian Ren , Sergey Tulyakov , Leonid Sigal

Diffusion models have exhibited impressive prowess in the text-to-image task. Recent methods add image-level structure controls, e.g., edge and depth maps, to manipulate the generation process together with text prompts to obtain desired…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Yibo Zhao , Liang Peng , Yang Yang , Zekai Luo , Hengjia Li , Yao Chen , Zheng Yang , Xiaofei He , Wei Zhao , qinglin lu , Boxi Wu , Wei Liu
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