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Text-to-image (T2I) models have significantly advanced in producing high-quality images. However, such models have the ability to generate images containing not-safe-for-work (NSFW) content, such as pornography, violence, political content,…

Cryptography and Security · Computer Science 2025-05-15 Longtian Wang , Xiaofei Xie , Tianlin Li , Yuhan Zhi , Chao Shen

Text-to-Image and Text-to-Video AI generation models are revolutionary technologies that use deep learning and natural language processing (NLP) techniques to create images and videos from textual descriptions. This paper investigates…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Aditi Singh

Text-to-image generation has evolved beyond single monolithic models to complex multi-component pipelines. These combine fine-tuned generators, adapters, upscaling blocks and even editing steps, leading to significant improvements in image…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Uri Gadot , Rinon Gal , Yftah Ziser , Gal Chechik , Shie Mannor

Text-image-to-video (TI2V) generation is a critical problem for controllable video generation using both semantic and visual conditions. Most existing methods typically add visual conditions to text-to-video (T2V) foundation models by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Bolin Lai , Sangmin Lee , Xu Cao , Xiang Li , James M. Rehg

We introduce LLaVA-Reward, an efficient reward model designed to automatically evaluate text-to-image (T2I) generations across multiple perspectives, leveraging pretrained multimodal large language models (MLLMs). Existing MLLM-based…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Shijie Zhou , Ruiyi Zhang , Huaisheng Zhu , Branislav Kveton , Yufan Zhou , Jiuxiang Gu , Jian Chen , Changyou Chen

Recent image generation schemes typically capture image distribution in a pre-constructed latent space relying on a frozen image tokenizer. Though the performance of tokenizer plays an essential role to the successful generation, its…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Kai Qiu , Xiang Li , Jason Kuen , Hao Chen , Xiaohao Xu , Jiuxiang Gu , Yinyi Luo , Bhiksha Raj , Zhe Lin , Marios Savvides

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

The proliferation of Large Language Models (LLMs) in real-world applications poses unprecedented risks of generating harmful, biased, or misleading information to vulnerable populations including LGBTQ+ individuals, single parents, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Tung Vu , Lam Nguyen , Quynh Dao

Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications. Since they are highly data-driven, relying on…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Patrick Schramowski , Manuel Brack , Björn Deiseroth , Kristian Kersting

Large Language Models (LLMs) have significantly advanced natural language processing (NLP) tasks but also pose ethical and societal risks due to their propensity to generate harmful content. Existing methods have limitations, including the…

Computation and Language · Computer Science 2025-05-22 Ximing Dong , Dayi Lin , Shaowei Wang , Ahmed E. Hassan

Text-to-image (T2I) models have recently experienced rapid development, achieving astonishing performance in terms of fidelity and textual alignment capabilities. However, given a long paragraph (up to 512 words), these generation models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Weijia Wu , Zhuang Li , Yefei He , Mike Zheng Shou , Chunhua Shen , Lele Cheng , Yan Li , Tingting Gao , Di Zhang

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Text-to-image (T2I) generative models have revolutionized content creation by transforming textual descriptions into high-quality images. However, these models are vulnerable to jailbreaking attacks, where carefully crafted prompts bypass…

Cryptography and Security · Computer Science 2025-06-26 Yingkai Dong , Xiangtao Meng , Ning Yu , Zheng Li , Shanqing Guo

Text-to-Image synthesis is the task of generating an image according to a specific text description. Generative Adversarial Networks have been considered the standard method for image synthesis virtually since their introduction. Denoising…

Computer Vision and Pattern Recognition · Computer Science 2023-05-18 Konstantina Nikolaidou , George Retsinas , Vincent Christlein , Mathias Seuret , Giorgos Sfikas , Elisa Barney Smith , Hamam Mokayed , Marcus Liwicki

Token-based masked generative models are gaining popularity for their fast inference time with parallel decoding. While recent token-based approaches achieve competitive performance to diffusion-based models, their generation performance is…

Machine Learning · Computer Science 2023-04-05 Jaewoong Lee , Sangwon Jang , Jaehyeong Jo , Jaehong Yoon , Yunji Kim , Jin-Hwa Kim , Jung-Woo Ha , Sung Ju Hwang

Diffusion-based text-to-image (T2I) models enable high-quality image generation but also pose significant risks of misuse, particularly in producing not-safe-for-work (NSFW) content. While prior detection methods have focused on filtering…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Fan Yang , Yihao Huang , Jiayi Zhu , Ling Shi , Geguang Pu , Jin Song Dong , Kailong Wang

Generating 3D human motions from text is a challenging yet valuable task. The key aspects of this task are ensuring text-motion consistency and achieving generation diversity. Although recent advancements have enabled the generation of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Zheng Qin , Yabing Wang , Minghui Yang , Sanping Zhou , Ming Yang , Le Wang

Recent AI systems have shown extremely powerful performance, even surpassing human performance, on various tasks such as information retrieval, language generation, and image generation based on large language models (LLMs). At the same…

Artificial Intelligence · Computer Science 2024-05-29 Minseon Kim , Hyomin Lee , Boqing Gong , Huishuai Zhang , Sung Ju Hwang

Despite remarkable progress in Text-to-Image models, many real-world applications require generating coherent image sets with diverse consistency requirements. Existing consistent methods often focus on a specific domain with specific…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Chengyou Jia , Xin Shen , Zhuohang Dang , Zhuohang Dang , Changliang Xia , Weijia Wu , Xinyu Zhang , Hangwei Qian , Ivor W. Tsang , Minnan Luo

Image-to-image (I2I) translation is usually carried out among discrete domains. However, image domains, often corresponding to a physical value, are usually continuous. In other words, images gradually change with the value, and there…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Qiusheng Huang , Xueqi Hu , Li Sun , Qingli Li