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Recent advances in Machine-Learning have led to the development of models that generate images based on a text description.Such large prompt-based text to image models (TTIs), trained on a considerable amount of data, allow the creation of…

Human-Computer Interaction · Computer Science 2023-03-23 Chinmay Kulkarni , Stefania Druga , Minsuk Chang , Alex Fiannaca , Carrie Cai , Michael Terry

One of the latest applications of Artificial Intelligence (AI) is to generate images from natural language descriptions. These generators are now becoming available and achieve impressive results that have been used for example in the front…

Computation and Language · Computer Science 2022-11-18 Pedro Reviriego , Elena Merino-Gómez

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

As generative AI systems rapidly improve, a key question emerges: how do users adapt to these changes, and when does such adaptation matter for realizing performance gains? Drawing on theories of dynamic capabilities and IT complements, we…

Human-Computer Interaction · Computer Science 2026-01-08 Eaman Jahani , Benjamin S. Manning , Joe Zhang , Hong-Yi TuYe , Mohammed Alsobay , Christos Nicolaides , Siddharth Suri , David Holtz

Text-to-Image (T2I) models have transformed visual content creation, producing highly realistic images from natural language prompts. However, concerns persist around their potential to replicate and magnify existing societal biases. To…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Sedat Porikli , Vedat Porikli

Well-designed prompts can guide text-to-image models to generate amazing images. However, the performant prompts are often model-specific and misaligned with user input. Instead of laborious human engineering, we propose prompt adaptation,…

Computation and Language · Computer Science 2024-01-01 Yaru Hao , Zewen Chi , Li Dong , Furu Wei

Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text prompts. Such text-based synthesis methods are particularly…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Amir Hertz , Ron Mokady , Jay Tenenbaum , Kfir Aberman , Yael Pritch , Daniel Cohen-Or

Text-to-image (T2I) models, while offering immense creative potential, are highly reliant on human intervention, posing significant usability challenges that often necessitate manual, iterative prompt engineering over often underspecified…

Artificial Intelligence · Computer Science 2025-09-16 Xingchen Wan , Han Zhou , Ruoxi Sun , Hootan Nakhost , Ke Jiang , Rajarishi Sinha , Sercan Ö. Arık

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

Text-to-Image (TTI) generative models have shown great progress in the past few years in terms of their ability to generate complex and high-quality imagery. At the same time, these models have been shown to suffer from harmful biases,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Aditya Chinchure , Pushkar Shukla , Gaurav Bhatt , Kiri Salij , Kartik Hosanagar , Leonid Sigal , Matthew Turk

Text-to-Image (T2I) generation has achieved remarkable progress in recent years. Meanwhile, reinforcement learning methods, particularly those based on Group Relative Policy Optimization (GRPO), have attracted widespread attention and been…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Baoteng Li , Xianghao Zang , Xinran Wang , Xiangyu Na , Zhixiang He , Hao Sun , Chi Zhang , Zhongjiang He , Tianwei Cao , Kongming Liang , Zhanyu Ma

Text-to-image (T2I) generation model has made significant advancements, resulting in high-quality images aligned with an input prompt. However, despite T2I generation's ability to generate fine-grained images, it still faces challenges in…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Taekyung Lee , Donggyu Lee , Myungjoo Kang

In this paper, we design and train a Generative Image-to-text Transformer, GIT, to unify vision-language tasks such as image/video captioning and question answering. While generative models provide a consistent network architecture between…

Computer Vision and Pattern Recognition · Computer Science 2022-12-19 Jianfeng Wang , Zhengyuan Yang , Xiaowei Hu , Linjie Li , Kevin Lin , Zhe Gan , Zicheng Liu , Ce Liu , Lijuan Wang

Text-to-image (T2I) models offer great potential for creating virtually limitless synthetic data, a valuable resource compared to fixed and finite real datasets. Previous works evaluate the utility of synthetic data from T2I models on three…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Zhang Xiaofeng , Aaron Courville , Michal Drozdzal , Adriana Romero-Soriano

Data-to-text (D2T) generation is the task of generating texts from structured inputs. We observed that when the same target sentence was repeated twice, Transformer (T5) based model generates an output made up of asymmetric sentences from…

Computation and Language · Computer Science 2022-08-10 Choonghan Kim , Gary Geunbae Lee

Editing images using natural language instructions has become a natural and expressive way to modify visual content; yet, evaluating the performance of such models remains challenging. Existing evaluation approaches often rely on image-text…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Yusu Qian , Jiasen Lu , Tsu-Jui Fu , Xinze Wang , Chen Chen , Yinfei Yang , Wenze Hu , Zhe Gan

Generative AI (GenAI) image tools are increasingly used in design practice, enabling rapid ideation but offering limited support for refinement tasks such as adjusting layout, scale, or visual attributes. While text prompts and inpainting…

Human-Computer Interaction · Computer Science 2026-02-10 Hyerim Park , Phuong Thao Tran , Andre Luckow , Ceenu George , Michael Sedlmair , Malin Eiband

Compositionality is a critical capability in Text-to-Image (T2I) models, as it reflects their ability to understand and combine multiple concepts from text descriptions. Existing evaluations of compositional capability rely heavily on…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xindi Wu , Dingli Yu , Yangsibo Huang , Olga Russakovsky , Sanjeev Arora

This research investigates the use of customized GPT models to enhance prompting proficiency among architecture students when generating AI-driven images. Prompt engineering is increasingly essential in architectural education due to the…

Human-Computer Interaction · Computer Science 2025-04-28 Juan David Salazar Rodriguez , Sam Conrad Joyce , Julfendi

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