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Masked generative models (MGMs) have shown impressive generative ability while providing an order of magnitude efficient sampling steps compared to continuous diffusion models. However, MGMs still underperform in image synthesis compared to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Jiwan Hur , Dong-Jae Lee , Gyojin Han , Jaehyun Choi , Yunho Jeon , Junmo Kim

Text-to-image (T2I) diffusion models have demonstrated impressive capabilities in generating high-quality images given a text prompt. However, ensuring the prompt-image alignment remains a considerable challenge, i.e., generating images…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Liyao Jiang , Negar Hassanpour , Mohammad Salameh , Mohan Sai Singamsetti , Fengyu Sun , Wei Lu , Di Niu

Diffusion-based text-to-video generation (T2V) or image-to-video (I2V) generation have emerged as a prominent research focus. However, there exists a challenge in integrating the two generative paradigms into a unified model. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xinyu Xiao , Binbin Yang , Tingtian Li , Yipeng Yu , Sen Lei

Despite the integration of safety alignment and external filters, text-to-image (T2I) generative systems are still susceptible to producing harmful content, such as sexual or violent imagery. This raises serious concerns about unintended…

Cryptography and Security · Computer Science 2025-12-09 Boheng Li , Junjie Wang , Yiming Li , Zhiyang Hu , Leyi Qi , Jianshuo Dong , Run Wang , Han Qiu , Zhan Qin , Tianwei Zhang

Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and higher…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Taegyeong Lee , Soyeong Kwon , Taehwan Kim

Text-to-image diffusion models have achieved remarkable performance in image synthesis, while the text interface does not always provide fine-grained control over certain image factors. For instance, changing a single token in the text can…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Chen Wu , Fernando De la Torre

Recent advancements in diffusion models have showcased their impressive capacity to generate visually striking images. Nevertheless, ensuring a close match between the generated image and the given prompt remains a persistent challenge. In…

Computer Vision and Pattern Recognition · Computer Science 2023-09-11 Yupeng Zhou , Daquan Zhou , Zuo-Liang Zhu , Yaxing Wang , Qibin Hou , Jiashi Feng

Text-to-image (T2I) generative models have achieved remarkable visual fidelity, yet remain vulnerable to generating unsafe content. Existing safety defenses typically intervene internally within the generative model, but suffer from severe…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Xiangtao Meng , Yingkai Dong , Ning Yu , Li Wang , Zheng Li , Shanqing Guo

Text-to-image (T2I) diffusion models have become prominent tools for generating high-fidelity images from text prompts. However, when trained on unfiltered internet data, these models can produce unsafe, incorrect, or stylistically…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Rohit Jena , Ali Taghibakhshi , Sahil Jain , Gerald Shen , Nima Tajbakhsh , Arash Vahdat

Closed-weight generative services are increasingly deployed through query-based APIs, where users can obtain generated outputs while model parameters remain inaccessible. However, such deployment does not prevent model stealing: an attacker…

Cryptography and Security · Computer Science 2026-05-22 Yilan Gao , Sida Huang , Hongyuan Zhang , Xuelong Li

Image diffusion models have been utilized in various tasks, such as text-to-image generation and controllable image synthesis. Recent research has introduced tuning methods that make subtle adjustments to the original models, yielding…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Zeyinzi Jiang , Chaojie Mao , Yulin Pan , Zhen Han , Jingfeng Zhang

Image synthesis approaches, e.g., generative adversarial networks, have been popular as a form of data augmentation in medical image analysis tasks. It is primarily beneficial to overcome the shortage of publicly accessible data and…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Shiyi Du , Xiaosong Wang , Yongyi Lu , Yuyin Zhou , Shaoting Zhang , Alan Yuille , Kang Li , Zongwei Zhou

Recent advances in text-to-image (T2I) diffusion models have enabled impressive image generation capabilities guided by text prompts. However, extending these techniques to video generation remains challenging, with existing text-to-video…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Weifeng Chen , Yatai Ji , Jie Wu , Hefeng Wu , Pan Xie , Jiashi Li , Xin Xia , Xuefeng Xiao , Liang Lin

Recent controllable generation approaches such as FreeControl and Diffusion Self-Guidance bring fine-grained spatial and appearance control to text-to-image (T2I) diffusion models without training auxiliary modules. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Kuan Heng Lin , Sicheng Mo , Ben Klingher , Fangzhou Mu , Bolei Zhou

Text-to-image generation (T2I) refers to the text-guided generation of high-quality images. In the past few years, T2I has attracted widespread attention and numerous works have emerged. In this survey, we comprehensively review 141 works…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Pengfei Yang , Ngai-Man Cheung , Xinda Ma

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

Text-to-image diffusion models have recently attracted the interest of many researchers, and inverting the diffusion process can play an important role in better understanding the generative process and how to engineer prompts in order to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Florinel-Alin Croitoru , Vlad Hondru , Radu Tudor Ionescu , Mubarak Shah

In the past years, we have witnessed the remarkable success of Text-to-Image (T2I) models and their widespread use on the web. Extensive research in making T2I models produce hyper-realistic images has led to new concerns, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Muhammad Shahid Muneer , Simon S. Woo

With the rapid advancement of intelligent transportation systems, text-driven image generation and editing techniques have demonstrated significant potential in providing rich, controllable visual scene data for applications such as traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Feng Lv , Haoxuan Feng , Zilu Zhang , Chunlong Xia , Yanfeng Li

Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from their training data, leading to the reproduction of unsafe content such as NSFW imagery and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Renyang Liu , Kangjie Chen , Han Qiu , Jie Zhang , Kwok-Yan Lam , Tianwei Zhang , See-Kiong Ng