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Conditional text-to-image generation is an active area of research, with many possible applications. Existing research has primarily focused on generating a single image from available conditioning information in one step. One practical…

Computer Vision and Pattern Recognition · Computer Science 2019-09-24 Alaaeldin El-Nouby , Shikhar Sharma , Hannes Schulz , Devon Hjelm , Layla El Asri , Samira Ebrahimi Kahou , Yoshua Bengio , Graham W. Taylor

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…

A picture is worth a thousand words, thus, it is crucial for conversational agents to understand, perceive, and effectively respond with pictures. However, we find that directly employing conventional image generation techniques is…

Computation and Language · Computer Science 2024-02-09 Xiaowen Sun , Jiazhan Feng , Yuxuan Wang , Yuxuan Lai , Xingyu Shen , Dongyan Zhao

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

Text-to-image models often struggle to generate images that precisely match textual prompts. Prior research has extensively studied the evaluation of image-text alignment in text-to-image generation. However, existing evaluations primarily…

Computation and Language · Computer Science 2025-06-11 Huixuan Zhang , Xiaojun Wan

Recent advancements in text-to-image (T2I) generation models have transformed the field. However, challenges persist in generating images that reflect demanding textual descriptions, especially for fine-grained details and unusual…

Multimedia · Computer Science 2025-02-21 Ran Li , Xiaomeng Jin , Heng ji

Large-scale generative models have shown impressive image-generation capabilities, propelled by massive data. However, this often inadvertently leads to the generation of harmful or inappropriate content and raises copyright concerns.…

Machine Learning · Computer Science 2025-03-11 Myeongseob Ko , Henry Li , Zhun Wang , Jonathan Patsenker , Jiachen T. Wang , Qinbin Li , Ming Jin , Dawn Song , Ruoxi Jia

Personalized text-to-image generation models enable users to create images that depict their individual possessions in diverse scenes, finding applications in various domains. To achieve the personalization capability, existing methods rely…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Yu Zeng , Vishal M. Patel , Haochen Wang , Xun Huang , Ting-Chun Wang , Ming-Yu Liu , Yogesh Balaji

Large-scale text-to-image models have demonstrated amazing ability to synthesize diverse and high-fidelity images. However, these models are often violated by several limitations. Firstly, they require the user to provide precise and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yupei Lin , Sen Zhang , Xiaojun Yang , Xiao Wang , Yukai Shi

Reading and repeatedly retelling a short story is a common and effective approach to learning the meanings and usages of target words. However, learners often struggle with comprehending, recalling, and retelling the story contexts of these…

Human-Computer Interaction · Computer Science 2024-05-27 Qiaoyi Chen , Siyu Liu , Kaihui Huang , Xingbo Wang , Xiaojuan Ma , Junkai Zhu , Zhenhui Peng

Novel architectures have recently improved generative image synthesis leading to excellent visual quality in various tasks. Of particular note is the field of ``AI-Art'', which has seen unprecedented growth with the emergence of powerful…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Robin Rombach , Andreas Blattmann , Björn Ommer

Text-to-image diffusion models have demonstrated remarkable capabilities in transforming textual prompts into coherent images, yet the computational cost of their inference remains a persistent challenge. To address this issue, we present…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yanwu Xu , Yang Zhao , Zhisheng Xiao , Tingbo Hou

Evaluating the quality of automatically generated image descriptions is a complex task that requires metrics capturing various dimensions, such as grammaticality, coverage, accuracy, and truthfulness. Although human evaluation provides…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Jia-Hong Huang , Hongyi Zhu , Yixian Shen , Stevan Rudinac , Evangelos Kanoulas

The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and fast generation capabilities, one of which is texture…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Raphael Bensadoun , Yanir Kleiman , Idan Azuri , Omri Harosh , Andrea Vedaldi , Natalia Neverova , Oran Gafni

Text-to-image generative models have made significant advancements in recent years; however, accurately capturing intricate details in textual prompts-such as entity missing, attribute binding errors, and incorrect relationships remains a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Amir Mohammad Izadi , Seyed Mohammad Hadi Hosseini , Soroush Vafaie Tabar , Ali Abdollahi , Armin Saghafian , Mahdieh Soleymani Baghshah

Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models still struggle with prompts that require rich world knowledge and implicit reasoning: both of which are critical for producing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Daoan Zhang , Che Jiang , Ruoshi Xu , Biaoxiang Chen , Zijian Jin , Yutian Lu , Jianguo Zhang , Liang Yong , Jiebo Luo , Shengda Luo

Recent advances in generative diffusion models have enabled text-controlled synthesis of realistic and diverse images with impressive quality. Despite these remarkable advances, the application of text-to-image generative models in computer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yulu Gan , Sungwoo Park , Alexander Schubert , Anthony Philippakis , Ahmed M. Alaa

In this work we propose a new computational framework, based on generative deep models, for synthesis of photo-realistic food meal images from textual list of its ingredients. Previous works on synthesis of images from text typically rely…

Computer Vision and Pattern Recognition · Computer Science 2020-02-27 Fangda Han , Ricardo Guerrero , Vladimir Pavlovic

In this work we propose a new computational framework, based on generative deep models, for synthesis of photo-realistic food meal images from textual descriptions of its ingredients. Previous works on synthesis of images from text…

Computer Vision and Pattern Recognition · Computer Science 2019-05-31 Fangda Han , Ricardo Guerrero , Vladimir Pavlovic

In recent years, the fashion industry has increasingly adopted AI technologies to enhance customer experience, driven by the proliferation of e-commerce platforms and virtual applications. Among the various tasks, virtual try-on and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Fulvio Sanguigni , Davide Morelli , Marcella Cornia , Rita Cucchiara