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The rapid advancement of diffusion models has enabled high-fidelity and semantically rich text-to-image generation; however, ensuring fairness and safety remains an open challenge. Existing methods typically improve fairness and safety at…

计算机视觉与模式识别 · 计算机科学 2025-10-09 Silpa Vadakkeeveetil Sreelatha , Sauradip Nag , Muhammad Awais , Serge Belongie , Anjan Dutta

Recent Text-to-Image (T2I) generation models such as Stable Diffusion and Imagen have made significant progress in generating high-resolution images based on text descriptions. However, many generated images still suffer from issues such as…

Text-to-Image (T2I) has been prevalent in recent years, with most common condition tasks having been optimized nicely. Besides, counterfactual Text-to-Image is obstructing us from a more versatile AIGC experience. For those scenes that are…

计算机视觉与模式识别 · 计算机科学 2025-05-21 Sifan Li , Ming Tao , Hao Zhao , Ling Shao , Hao Tang

While Text-To-Video (T2V) models have advanced rapidly, they continue to struggle with generating legible and coherent text within videos. In particular, existing models often fail to render correctly even short phrases or words and…

计算机视觉与模式识别 · 计算机科学 2025-11-11 Ziyang Liu , Kevin Valencia , Justin Cui

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…

计算机视觉与模式识别 · 计算机科学 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

Recent advancements in text-to-image (T2I) models have unlocked a wide range of applications but also present significant risks, particularly in their potential to generate unsafe content. To mitigate this issue, researchers have developed…

计算机视觉与模式识别 · 计算机科学 2025-01-17 Yong-Hyun Park , Sangdoo Yun , Jin-Hwa Kim , Junho Kim , Geonhui Jang , Yonghyun Jeong , Junghyo Jo , Gayoung Lee

Generative Artificial Intelligence (AI) has created unprecedented opportunities for creative expression, education, and research. Text-to-image systems such as DALL.E, Stable Diffusion, and Midjourney can now convert ideas into visuals…

人工智能 · 计算机科学 2025-12-16 Dang Phuong Nam , Nguyen Kieu , Pham Thanh Hieu

Text-to-image generative models have recently garnered significant attention due to their ability to generate images based on prompt descriptions. While these models have shown promising performance, concerns have been raised regarding the…

计算机视觉与模式识别 · 计算机科学 2025-09-09 Meiling Li , Zhenxing Qian , Xinpeng Zhang

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…

计算机视觉与模式识别 · 计算机科学 2026-01-21 Xiangtao Meng , Yingkai Dong , Ning Yu , Li Wang , Zheng Li , Shanqing Guo

We introduce Value Sign Flip (VSF), a simple and efficient method for incorporating negative prompt guidance in few-step diffusion and flow-matching image generation models. Unlike existing approaches such as classifier-free guidance (CFG),…

计算机视觉与模式识别 · 计算机科学 2026-02-20 Wenqi Guo , Shan Du

Text-to-image models take a sentence (i.e., prompt) and generate images associated with this input prompt. These models have created award wining-art, videos, and even synthetic datasets. However, text-to-image (T2I) models can generate…

计算与语言 · 计算机科学 2023-06-12 Alexander Lin , Lucas Monteiro Paes , Sree Harsha Tanneru , Suraj Srinivas , Himabindu Lakkaraju

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…

计算机视觉与模式识别 · 计算机科学 2024-02-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang

With advances in the quality of text-to-image (T2I) models has come interest in benchmarking their prompt faithfulness -- the semantic coherence of generated images to the prompts they were conditioned on. A variety of T2I faithfulness…

计算机视觉与模式识别 · 计算机科学 2024-11-01 Michael Saxon , Fatima Jahara , Mahsa Khoshnoodi , Yujie Lu , Aditya Sharma , William Yang Wang

Text-to-Image models, including Stable Diffusion, have significantly improved in generating images that are highly semantically aligned with the given prompts. However, existing models may fail to produce appropriate images for the cultural…

计算机视觉与模式识别 · 计算机科学 2025-05-20 Suchae Jeong , Inseong Choi , Youngsik Yun , Jihie Kim

Text-to-image (T2I) models such as Stable Diffusion and DALLE remain susceptible to generating harmful or Not-Safe-For-Work (NSFW) content under jailbreak attacks despite deployed safety filters. Existing jailbreak attacks either rely on…

计算机视觉与模式识别 · 计算机科学 2026-03-27 Haolun Zheng , Yu He , Tailun Chen , Shuo Shao , Zhixuan Chu , Hongbin Zhou , Lan Tao , Zhan Qin , Kui Ren

Continual learning aims to refine model parameters for new tasks while retaining knowledge from previous tasks. Recently, prompt-based learning has emerged to leverage pre-trained models to be prompted to learn subsequent tasks without the…

计算机视觉与模式识别 · 计算机科学 2024-03-19 Jisu Han , Jaemin Na , Wonjun Hwang

The rapid evolution of text-to-image (T2I) models has enabled high-fidelity visual synthesis on a global scale. However, these advancements have introduced significant security risks, particularly regarding the generation of harmful…

密码学与安全 · 计算机科学 2026-01-16 Wonwoo Choi , Minjae Seo , Minkyoo Song , Hwanjo Heo , Seungwon Shin , Myoungsung You

The recent advances in diffusion models (DMs) have revolutionized the generation of realistic and complex images. However, these models also introduce potential safety hazards, such as producing harmful content and infringing data…

计算机视觉与模式识别 · 计算机科学 2024-07-09 Yimeng Zhang , Jinghan Jia , Xin Chen , Aochuan Chen , Yihua Zhang , Jiancheng Liu , Ke Ding , Sijia Liu

Recent text-to-image (T2I) diffusion models show outstanding performance in generating high-quality images conditioned on textual prompts. However, they fail to semantically align the generated images with the prompts due to their limited…

计算机视觉与模式识别 · 计算机科学 2023-12-15 Ruichen Wang , Zekang Chen , Chen Chen , Jian Ma , Haonan Lu , Xiaodong Lin

Text-to-image (T2I) models are increasingly popular, producing a large share of AI-generated images online. To compare model quality, voting-based leaderboards have become the standard, relying on anonymized model outputs for fairness. In…

计算机视觉与模式识别 · 计算机科学 2026-01-15 Ali Naseh , Yuefeng Peng , Anshuman Suri , Harsh Chaudhari , Alina Oprea , Amir Houmansadr