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Related papers: Evaluating Text-to-Image Generative Models: An Emp…

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While synthetic data has proven effective for improving scientific reasoning in the text domain, multimodal reasoning remains constrained by the difficulty of synthesizing scientifically rigorous images. Existing Text-to-Image (T2I) models…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Honglin Lin , Chonghan Qin , Zheng Liu , Qizhi Pei , Yu Li , Zhanping Zhong , Xin Gao , Yanfeng Wang , Conghui He , Lijun Wu

The crux of text-to-image synthesis stems from the difficulty of preserving the cross-modality semantic consistency between the input text and the synthesized image. Typical methods, which seek to model the text-to-image mapping directly,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-15 Jiadong Liang , Wenjie Pei , Feng Lu

We address the task of advertisement image generation and introduce three evaluation metrics to assess Creativity, prompt Alignment, and Persuasiveness (CAP) in generated advertisement images. Despite recent advancements in Text-to-Image…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Aysan Aghazadeh , Adriana Kovashka

Text-to-image generative models have shown remarkable progress in producing diverse and photorealistic outputs. In this paper, we present a comprehensive analysis of their effectiveness in creating synthetic portraits that accurately…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Alexey A. Novikov , Miroslav Vranka , François David , Artem Voronin

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-to-image (T2I) diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the strong generalization capabilities of these models can inadvertently led they to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Die Chen , Zhiwen Li , Cen Chen , Xiaodan Li , Jinyan Ye

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

The field of text-to-image (T2I) generation has garnered significant attention both within the research community and among everyday users. Despite the advancements of T2I models, a common issue encountered by users is the need for…

Computation and Language · Computer Science 2023-10-31 Wanrong Zhu , Xinyi Wang , Yujie Lu , Tsu-Jui Fu , Xin Eric Wang , Miguel Eckstein , William Yang Wang

Generative AI is transforming image synthesis, enabling the creation of high-quality, diverse, and photorealistic visuals across industries like design, media, healthcare, and autonomous systems. Advances in techniques such as…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Fouad Bousetouane

Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance. However, these T2I models still struggle to produce images that are aesthetically pleasing, geometrically…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jianshu Guo , Wenhao Chai , Jie Deng , Hsiang-Wei Huang , Tian Ye , Yichen Xu , Jiawei Zhang , Jenq-Neng Hwang , Gaoang Wang

Despite the high-quality results of text-to-image generation, stereotypical biases have been spotted in their generated contents, compromising the fairness of generative models. In this work, we propose to learn adaptive inclusive tokens to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Xinyu Hou , Xiaoming Li , Chen Change Loy

We introduce ``Idea to Image,'' a system that enables multimodal iterative self-refinement with GPT-4V(ision) for automatic image design and generation. Humans can quickly identify the characteristics of different text-to-image (T2I) models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Zhengyuan Yang , Jianfeng Wang , Linjie Li , Kevin Lin , Chung-Ching Lin , Zicheng Liu , Lijuan Wang

Text to image generation methods (T2I) are widely popular in generating art and other creative artifacts. While visual hallucinations can be a positive factor in scenarios where creativity is appreciated, such artifacts are poorly suited…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Rodrigo Valerio , Joao Bordalo , Michal Yarom , Yonatan Bitton , Idan Szpektor , Joao Magalhaes

Recent text-to-image (T2I) diffusion and flow-matching models can produce highly realistic images from natural language prompts. In practical scenarios, T2I systems are often run in a ``generate--then--select'' mode: many seeds are sampled…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Huanlei Guo , Hongxin Wei , Bingyi Jing

Text-to-image models, which can generate high-quality images based on textual input, have recently enabled various content-creation tools. Despite significantly affecting a wide range of downstream applications, the distributions of these…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Yanzhe Zhang , Lu Jiang , Greg Turk , Diyi Yang

Text-to-image synthesis aims to automatically generate images according to text descriptions given by users, which is a highly challenging task. The main issues of text-to-image synthesis lie in two gaps: the heterogeneous and homogeneous…

Computer Vision and Pattern Recognition · Computer Science 2018-08-22 Mingkuan Yuan , Yuxin Peng

Recent advances in deep learning and on-device inference could transform routine screening for skin cancers. Along with the anticipated benefits of this technology, potential dangers arise from unforeseen and inherent biases. A significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Ko Watanabe , Stanislav Frolov , Aya Hassan , David Dembinsky , Adriano Lucieri , Andreas Dengel

Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style benchmarks mainly focus on understanding and reasoning tasks, and current generation benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Zhaokai Wang , Penghao Yin , Xiangyu Zhao , Changyao Tian , Yu Qiao , Wenhai Wang , Jifeng Dai , Gen Luo

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation, ignoring the editing, restricting them from synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yunjie Wu , Yapeng Meng , Zhipeng Hu , Lincheng Li , Haoqian Wu , Kun Zhou , Weiwei Xu , Xin Yu

This work presents an open-source unified benchmarking and evaluation framework for text-to-image generation models, with a particular focus on the impact of metadata augmented prompts. Leveraging the DeepFashion-MultiModal dataset, we…

Graphics · Computer Science 2025-05-09 Kapil Wanaskar , Gaytri Jena , Magdalini Eirinaki