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Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Narek Tumanyan , Michal Geyer , Shai Bagon , Tali Dekel

Scaling up model and data size has been quite successful for the evolution of LLMs. However, the scaling law for the diffusion based text-to-image (T2I) models is not fully explored. It is also unclear how to efficiently scale the model for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Hao Li , Yang Zou , Ying Wang , Orchid Majumder , Yusheng Xie , R. Manmatha , Ashwin Swaminathan , Zhuowen Tu , Stefano Ermon , Stefano Soatto

The risk of misusing text-to-image generative models for malicious uses, especially due to the open-source development of such models, has become a serious concern. As a risk mitigation strategy, attributing generative models with neural…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Murthy L , Subarna Tripathi

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

Text-to-image generative models are becoming increasingly popular and accessible to the general public. As these models see large-scale deployments, it is necessary to deeply investigate their safety and fairness to not disseminate and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Moreno D'Incà , Elia Peruzzo , Massimiliano Mancini , Dejia Xu , Vidit Goel , Xingqian Xu , Zhangyang Wang , Humphrey Shi , Nicu Sebe

The surge in the popularity of text-to-image generators (T2Is) has been matched by extensive research into ensuring fairness and equitable outcomes, with a focus on how they impact society. However, such work has typically focused on…

Computers and Society · Computer Science 2024-08-06 Sourojit Ghosh

We do not pursue a novel method in this paper, but aim to study if a modern text-to-image diffusion model can tailor any task-adaptive image classifier across domains and categories. Existing domain adaptive image classification works…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Weijie Chen , Haoyu Wang , Shicai Yang , Lei Zhang , Wei Wei , Yanning Zhang , Luojun Lin , Di Xie , Yueting Zhuang

Deep generative models are becoming increasingly powerful, now generating diverse high fidelity photo-realistic samples given text prompts. Have they reached the point where models of natural images can be used for generative data…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Shekoofeh Azizi , Simon Kornblith , Chitwan Saharia , Mohammad Norouzi , David J. Fleet

Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

Image-to-Image (I2I) translation is a heated topic in academia, and it also has been applied in real-world industry for tasks like image synthesis, super-resolution, and colorization. However, traditional I2I translation methods train data…

Computer Vision and Pattern Recognition · Computer Science 2020-10-28 Jialu Huang , Jing Liao , Sam Kwong

Recent advancements in text-guided diffusion models have unlocked powerful image manipulation capabilities. However, applying these methods to real images necessitates the inversion of the images into the domain of the pretrained diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Daniel Garibi , Or Patashnik , Andrey Voynov , Hadar Averbuch-Elor , Daniel Cohen-Or

Existing text-to-image (T2I) diffusion models face several limitations, including large model sizes, slow runtime, and low-quality generation on mobile devices. This paper aims to address all of these challenges by developing an extremely…

The problem of text-guided image generation is a complex task in Computer Vision, with various applications, including creating visually appealing artwork and realistic product images. One popular solution widely used for this task is the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Halil Faruk Karagoz , Gulcin Baykal , Irem Arikan Eksi , Gozde Unal

Text-to-Image (T2I) Diffusion Models (DMs) have garnered widespread attention for their impressive advancements in image generation. However, their growing popularity has raised ethical and social concerns related to key non-functional…

Machine Learning · Computer Science 2025-07-22 Yi Zhang , Zhen Chen , Chih-Hong Cheng , Wenjie Ruan , Xiaowei Huang , Dezong Zhao , David Flynn , Siddartha Khastgir , Xingyu Zhao

Generative artificial intelligence (AI) refers to algorithms that create synthetic but realistic output. Diffusion models currently offer state of the art performance in generative AI for images. They also form a key component in more…

Machine Learning · Computer Science 2023-12-27 Catherine F. Higham , Desmond J. Higham , Peter Grindrod

Recent advances in text-to-image (T2I) diffusion models have significantly improved the quality of generated images. However, providing efficient control over individual subjects, particularly the attributes characterizing them, remains a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Stefan Andreas Baumann , Felix Krause , Michael Neumayr , Nick Stracke , Melvin Sevi , Vincent Tao Hu , Björn Ommer

Generative diffusion models offer a natural choice for data augmentation when training complex vision models. However, ensuring reliability of their generative content as augmentation samples remains an open challenge. Despite a number of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Khawar Islam , Naveed Akhtar

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

Diffusion-based text-to-image generation models like GLIDE and DALLE-2 have gained wide success recently for their superior performance in turning complex text inputs into images of high quality and wide diversity. In particular, they are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-16 Zhihong Pan , Xin Zhou , Hao Tian

Large-scale text-to-image models have demonstrated amazing ability to synthesize diverse and high-fidelity images. However, these models are often violated by several limitations. Firstly, they require the user to provide precise and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yupei Lin , Sen Zhang , Xiaojun Yang , Xiao Wang , Yukai Shi