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The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Given a small number of images of a subject, personalized image generation techniques can fine-tune large pre-trained text-to-image diffusion models to generate images of the subject in novel contexts, conditioned on text prompts. In doing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Shwetha Ram , Tal Neiman , Qianli Feng , Andrew Stuart , Son Tran , Trishul Chilimbi

Recently, there have been significant improvements in the quality and performance of text-to-image generation, largely due to the impressive results attained by diffusion models. However, text-to-image diffusion models sometimes struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Wonjun Kang , Kevin Galim , Hyung Il Koo , Nam Ik Cho

The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

Recently, diffusion-based deep generative models (e.g., Stable Diffusion) have shown impressive results in text-to-image synthesis. However, current text-to-image models often require multiple passes of prompt engineering by humans in order…

Computation and Language · Computer Science 2023-11-14 Tingfeng Cao , Chengyu Wang , Bingyan Liu , Ziheng Wu , Jinhui Zhu , Jun Huang

Generative modeling is widely regarded as one of the most essential problems in today's AI community, with text-to-image generation having gained unprecedented real-world impacts. Among various approaches, diffusion models have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xuyang Guo , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang , Zhen Zhuang

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…

Diffusion distillation has dramatically accelerated class-conditional image synthesis, but its applicability to open-ended text-to-image (T2I) generation is still unclear. We present the first systematic study that adapts and compares…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Yifan Pu , Yizeng Han , Zhiwei Tang , Jiasheng Tang , Fan Wang , Bohan Zhuang , Gao Huang

Text-to-Image (T2I) models have recently achieved remarkable success in generating images from textual descriptions. However, challenges still persist in accurately rendering complex scenes where actions and interactions form the primary…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Vatsal Malaviya , Agneet Chatterjee , Maitreya Patel , Yezhou Yang , Chitta Baral

Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Fanyue Wei , Wei Zeng , Zhenyang Li , Dawei Yin , Lixin Duan , Wen Li

Diffusion models have revitalized the image generation domain, playing crucial roles in both academic research and artistic expression. With the emergence of new diffusion models, assessing the performance of text-to-image models has become…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Chutian Meng , Fan Ma , Jiaxu Miao , Chi Zhang , Yi Yang , Yueting Zhuang

Text-to-image generation models that generate images based on prompt descriptions have attracted an increasing amount of attention during the past few months. Despite their encouraging performance, these models raise concerns about the…

Cryptography and Security · Computer Science 2023-01-10 Zeyang Sha , Zheng Li , Ning Yu , Yang Zhang

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai

Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic images. Despite the progress, these models still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Oscar Mañas , Pietro Astolfi , Melissa Hall , Candace Ross , Jack Urbanek , Adina Williams , Aishwarya Agrawal , Adriana Romero-Soriano , Michal Drozdzal

Text-to-image diffusion models have demonstrated remarkable capability in generating realistic images from arbitrary text prompts. However, they often produce inconsistent results for compositional prompts such as "two dogs" or "a penguin…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shuangqi Li , Hieu Le , Jingyi Xu , Mathieu Salzmann

Taking advantage of the many recent advances in deep learning, text-to-image generative models currently have the merit of attracting the general public attention. Two of these models, DALL-E 2 and Imagen, have demonstrated that highly…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Robin Zbinden

Text-to-image diffusion models, such as Stable Diffusion, have demonstrated remarkable capabilities in generating high-quality and diverse images from natural language prompts. However, recent studies reveal that these models often…

Machine Learning · Computer Science 2025-10-27 Zihao Fu , Ryan Brown , Shun Shao , Kai Rawal , Eoin Delaney , Chris Russell

Modern text-to-image (T2I) diffusion models can generate images with remarkable realism and creativity. These advancements have sparked research in fake image detection and attribution, yet prior studies have not fully explored the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Katherine Xu , Lingzhi Zhang , Jianbo Shi

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) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased. Existing safety methods typically refine prompts using…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Jinwoo Jeon , JunHyeok Oh , Hayeong Lee , Byung-Jun Lee