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In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

Generative artificial intelligence (GenAI) has made significant progress in understanding world knowledge and generating content from human languages across various modalities, like text-to-text large language models, text-to-image stable…

Machine Learning · Computer Science 2025-03-27 Zexi Li , Lingzhi Gao , Chao Wu

Text-to-image (T2I) diffusion models have shown significant success in personalized text-to-image generation, which aims to generate novel images with human identities indicated by the reference images. Despite promising identity fidelity…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Yuxiang Wei , Zhilong Ji , Jinfeng Bai , Hongzhi Zhang , Lei Zhang , Wangmeng Zuo

Text-to-image (T2I) models have recently gained widespread adoption. This has spurred concerns about safeguarding intellectual property rights and an increasing demand for mechanisms that prevent the generation of specific artistic styles.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anand Kumar , Jiteng Mu , Nuno Vasconcelos

Large-scale text-to-image diffusion models have achieved great success in synthesizing high-quality and diverse images given target text prompts. Despite the revolutionary image generation ability, current state-of-the-art models still…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Jingyuan Zhu , Huimin Ma , Jiansheng Chen , Jian Yuan

The popularization of Text-to-Image (T2I) diffusion models enables the generation of high-quality images from text descriptions. However, generating diverse customized images with reference visual attributes remains challenging. This work…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Brian Nlong Zhao , Yuhang Xiao , Jiashu Xu , Xinyang Jiang , Yifan Yang , Dongsheng Li , Laurent Itti , Vibhav Vineet , Yunhao Ge

Diffusion models for Text-to-Image (T2I) conditional generation have recently achieved tremendous success. Yet, aligning these models with user's intentions still involves a laborious trial-and-error process, and this challenging alignment…

Machine Learning · Computer Science 2025-02-12 Chao Wang , Giulio Franzese , Alessandro Finamore , Massimo Gallo , Pietro Michiardi

Text-to-image (T2I) generative models, such as Stable Diffusion and DALL-E, have shown remarkable proficiency in producing high-quality, realistic, and natural images from textual descriptions. However, these models sometimes fail to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Arash Marioriyad , Parham Rezaei , Mahdieh Soleymani Baghshah , Mohammad Hossein Rohban

To replicate the success of text-to-image (T2I) generation, recent works employ large-scale video datasets to train a text-to-video (T2V) generator. Despite their promising results, such paradigm is computationally expensive. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Jay Zhangjie Wu , Yixiao Ge , Xintao Wang , Weixian Lei , Yuchao Gu , Yufei Shi , Wynne Hsu , Ying Shan , Xiaohu Qie , Mike Zheng Shou

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion and video editing. A specialized area within generative…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Jiaxin Cheng , Zixu Zhao , Tong He , Tianjun Xiao , Yicong Zhou , Zheng Zhang

Recent advances in text-to-image (T2I) diffusion models have enabled impressive generative capabilities, but they also raise significant safety concerns due to the potential to produce harmful or undesirable content. While concept erasure…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Nanxiang Jiang , Zhaoxin Fan , Enhan Kang , Daiheng Gao , Yun Zhou , Yanxia Chang , Zheng Zhu , Yeying Jin , Wenjun Wu

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Geonung Kim , Beomsu Kim , Eunhyeok Park , Sunghyun Cho

Text-to-Image (T2I) models have demonstrated impressive capabilities in generating high-quality and diverse visual content from natural language prompts. However, uncontrolled reproduction of sensitive, copyrighted, or harmful imagery poses…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Yiwei Xie , Ping Liu , Zheng Zhang

While recent advancements in generative modeling have significantly improved text-image alignment, some residual misalignment between text and image representations still remains. Some approaches address this issue by fine-tuning models in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Jaa-Yeon Lee , Byunghee Cha , Jeongsol Kim , Jong Chul Ye

Personalized text-to-image generation lets users fine-tune diffusion models into repositories of concept-specific checkpoints, but serving these repositories efficiently is difficult for two reasons: natural-language requests are often…

Artificial Intelligence · Computer Science 2026-03-25 Qirui Wang , Qi Guo , Yiding Sun , Junkai Yang , Dongxu Zhang , Shanmin Pang , Qing Guo

Recent advancements in Virtual Try-On (VTO) have demonstrated exceptional efficacy in generating realistic images and preserving garment details, largely attributed to the robust generative capabilities of text-to-image (T2I) diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhenchen Wan , Yanwu Xu , Zhaoqing Wang , Feng Liu , Tongliang Liu , Mingming Gong

Text-to-image (T2I) diffusion models have shown remarkable success in generating high-quality images from text prompts. Recent efforts extend these models to incorporate conditional images (e.g., canny edge) for fine-grained spatial…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Liheng Zhang , Lexi Pang , Hang Ye , Xiaoxuan Ma , Yizhou Wang

Text-to-image (T2I) diffusion models such as SDXL and FLUX have achieved impressive photorealism, yet small-scale distortions remain pervasive in limbs, face, text and so on. Existing refinement approaches either perform costly iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Shaocheng Shen , Jianfeng Liang , Chunlei Cai , Cong Geng , Huiyu Duan , Xiaoyun Zhang , Qiang Hu , Guangtao Zhai

In recent years, text-to-image (T2I) diffusion models have gained significant attention for their ability to generate high quality images reflecting text prompts. However, their growing popularity has also led to the emergence of backdoor…

Cryptography and Security · Computer Science 2025-08-05 Shengfang Zhai , Jiajun Li , Yue Liu , Huanran Chen , Zhihua Tian , Wenjie Qu , Qingni Shen , Ruoxi Jia , Yinpeng Dong , Jiaheng Zhang

Recent advancements in diffusion models trained on large-scale data have enabled the generation of indistinguishable human-level images, yet they often produce harmful content misaligned with human values, e.g., social bias, and offensive…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Xingqi Wang , Xiaoyuan Yi , Xing Xie , Jia Jia