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The motivation of our research is to explore the possibilities of automatic sound-to-image (S2I) translation for enabling a human receiver to visually infer the occurrence of sound related events. We expect the computer to 'imagine' the…

Sound · Computer Science 2022-03-10 Leonardo A. Fanzeres , Climent Nadeu

Recent text-to-image (T2I) generation models have demonstrated impressive capabilities in creating images from text descriptions. However, these T2I generation models often fall short of generating images that precisely match the details of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Jialu Li , Jaemin Cho , Yi-Lin Sung , Jaehong Yoon , Mohit Bansal

Text-to-Image (T2I) diffusion models are widely recognized for their ability to generate high-quality and diverse images based on text prompts. However, despite recent advances, these models are still prone to generating unsafe images…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Jiangweizhi Peng , Zhiwei Tang , Gaowen Liu , Charles Fleming , Mingyi Hong

Blending visual and textual concepts into a new visual concept is a unique and powerful trait of human beings that can fuel creativity. However, in practice, cross-modal conceptual blending for humans is prone to cognitive biases, like…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Wonwoong Cho , Yanxia Zhang , Yan-Ying Chen , David I. Inouye

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

Text-to-Image (T2I) generation has made significant advancements with the advent of diffusion models. These models exhibit remarkable abilities to produce images based on textual prompts. Current T2I models allow users to specify object…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Muhammad Atif Butt , Kai Wang , Javier Vazquez-Corral , Joost van de Weijer

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transformer backbones. Although there have been efforts to control…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Liang Chen , Shuai Bai , Wenhao Chai , Weichu Xie , Haozhe Zhao , Leon Vinci , Junyang Lin , Baobao Chang

Recent advances in personalized image generation allow a pre-trained text-to-image model to learn a new concept from a set of images. However, existing personalization approaches usually require heavy test-time finetuning for each concept,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Jing Shi , Wei Xiong , Zhe Lin , Hyun Joon Jung

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

Text-to-image (T2I) models have significantly advanced the development of artificial intelligence, enabling the generation of high-quality images in diverse contexts based on specific text prompts. However, existing T2I-based methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Salaheldin Mohamed , Dong Han , Yong Li

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

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

While modern text-to-image (T2I) models excel at generating images from intricate prompts, they struggle to capture the key details when the inputs are descriptive paragraphs. This limitation stems from the prevalence of concise captions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Jen-Yuan Huang , Tong Lin , Yilun Du

Research on text-to-image generation has witnessed significant progress in generating diverse and photo-realistic images, driven by diffusion and auto-regressive models trained on large-scale image-text data. Though state-of-the-art models…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Wenhu Chen , Hexiang Hu , Chitwan Saharia , William W. Cohen

Despite advances in generation quality, current text-to-image (T2I) models often lack diversity, generating homogeneous outputs. This work introduces a framework to address the need for robust diversity evaluation in T2I models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Isabela Albuquerque , Ira Ktena , Olivia Wiles , Ivana Kajić , Amal Rannen-Triki , Cristina Vasconcelos , Aida Nematzadeh

The practical use of text-to-image generation has evolved from simple, monolithic models to complex workflows that combine multiple specialized components. While workflow-based approaches can lead to improved image quality, crafting…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Rinon Gal , Adi Haviv , Yuval Alaluf , Amit H. Bermano , Daniel Cohen-Or , Gal Chechik

Image colorization has been attracting the research interests of the community for decades. However, existing methods still struggle to provide satisfactory colorized results given grayscale images due to a lack of human-like global…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Hanyuan Liu , Jinbo Xing , Minshan Xie , Chengze Li , Tien-Tsin Wong

Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expanding this progress to video generation is still in its…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Hila Chefer , Shiran Zada , Roni Paiss , Ariel Ephrat , Omer Tov , Michael Rubinstein , Lior Wolf , Tali Dekel , Tomer Michaeli , Inbar Mosseri

Text-to-image (T2I) models are well known for their ability to produce highly realistic images, while multimodal large language models (MLLMs) are renowned for their proficiency in understanding and integrating multiple modalities. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Jian Ma , Qirong Peng , Xu Guo , Chen Chen , Haonan Lu , Zhenyu Yang

The recent advancement of large and powerful models with Text-to-Image (T2I) generation abilities -- such as OpenAI's DALLE-3 and Google's Gemini -- enables users to generate high-quality images from textual prompts. However, it has become…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yixin Wan , Arjun Subramonian , Anaelia Ovalle , Zongyu Lin , Ashima Suvarna , Christina Chance , Hritik Bansal , Rebecca Pattichis , Kai-Wei Chang