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Text-to-Image (T2I) generative models are becoming increasingly crucial due to their ability to generate high-quality images, but also raise concerns about social biases, particularly in human image generation. Sociological research has…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hanjun Luo , Haoyu Huang , Ziye Deng , Xinfeng Li , Hewei Wang , Yingbin Jin , Yang Liu , Wenyuan Xu , Zuozhu Liu

Text-to-Image (T2I) generation is enabling new applications that support creators, designers, and general end users of productivity software by generating illustrative content with high photorealism starting from a given descriptive text as…

Computers and Society · Computer Science 2023-04-14 Ranjita Naik , Besmira Nushi

Evidence shows that text-to-image (T2I) models disproportionately reflect Western cultural norms, amplifying misrepresentation and harms to minority groups. However, evaluating cultural sensitivity is inherently complex due to its fluid and…

Text-to-image (T2I) models exhibit a significant yet under-explored "brand bias", a tendency to generate contents featuring dominant commercial brands from generic prompts, posing ethical and legal risks. We propose CIDER, a novel,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Fangjian Shen , Zifeng Liang , Chao Wang , Wushao Wen

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

Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting to be integrated into higher-impact pipelines. Since generated images tend to reinforce…

Computers and Society · Computer Science 2026-05-14 Jose Luna , Yankun Wu , Xiaofei Xie , Noa Garcia

State-of-the-art T2I models are capable of generating high-resolution images given textual prompts. However, they still struggle with accurately depicting compositional scenes that specify multiple objects, attributes, and spatial…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Yixin Wan , Kai-Wei Chang

In this paper, we conduct a study on the state-of-the-art methods for text-to-image synthesis and propose a framework to evaluate these methods. We consider syntheses where an image contains a single or multiple objects. Our study outlines…

Computer Vision and Pattern Recognition · Computer Science 2022-07-20 Tan M. Dinh , Rang Nguyen , Binh-Son Hua

The unprecedented photorealistic results achieved by recent text-to-image generative systems and their increasing use as plug-and-play content creation solutions make it crucial to understand their potential biases. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Melissa Hall , Candace Ross , Adina Williams , Nicolas Carion , Michal Drozdzal , Adriana Romero Soriano

As text-to-image models become increasingly prevalent, ensuring their equitable performance across diverse cultural contexts is critical. Efforts to mitigate cross-cultural biases have been hampered by trade-offs, including a loss in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Arnav Yayavaram , Siddharth Yayavaram , Simran Khanuja , Michael Saxon , Graham Neubig

Recent progress in Text-to-Image (T2I) generative models has enabled high-quality image generation. As performance and accessibility increase, these models are gaining significant attraction and popularity: ensuring their fairness and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Moreno D'Incà , Elia Peruzzo , Massimiliano Mancini , Xingqian Xu , Humphrey Shi , Nicu Sebe

With the growing adoption of Text-to-Image (TTI) systems, the social biases of these models have come under increased scrutiny. Herein we conduct a systematic investigation of one such source of bias for diffusion models: embedding spaces.…

Machine Learning · Computer Science 2024-09-17 Sahil Kuchlous , Marvin Li , Jeffrey G. Wang

Text-to-Image (T2I) models are being increasingly adopted in diverse global communities where they create visual representations of their unique cultures. Current T2I benchmarks primarily focus on faithfulness, aesthetics, and realism of…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Nithish Kannen , Arif Ahmad , Marco Andreetto , Vinodkumar Prabhakaran , Utsav Prabhu , Adji Bousso Dieng , Pushpak Bhattacharyya , Shachi Dave

The surge in the popularity of text-to-image generators (T2Is) has been matched by extensive research into ensuring fairness and equitable outcomes, with a focus on how they impact society. However, such work has typically focused on…

Computers and Society · Computer Science 2024-08-06 Sourojit Ghosh

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

Text-to-Image (T2I) models have recently gained significant attention due to their ability to generate high-quality images and are consequently used in a wide range of applications. However, there are concerns about the gender bias of these…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Yunbo Lyu , Zhou Yang , Yuqing Niu , Jing Jiang , David Lo

Text-to-image generation (T2I) refers to the text-guided generation of high-quality images. In the past few years, T2I has attracted widespread attention and numerous works have emerged. In this survey, we comprehensively review 141 works…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Pengfei Yang , Ngai-Man Cheung , Xinda Ma

While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reasoning such as logic and comparison. In this work, we conduct…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Baiqi Li , Zhiqiu Lin , Deepak Pathak , Jiayao Li , Yixin Fei , Kewen Wu , Tiffany Ling , Xide Xia , Pengchuan Zhang , Graham Neubig , Deva Ramanan

Text-to-image (T2I) models have garnered significant attention for generating high-quality images aligned with text prompts. However, rapid T2I model advancements reveal limitations in early benchmarks, lacking comprehensive evaluations,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Jingjing Chang , Yixiao Fang , Peng Xing , Shuhan Wu , Wei Cheng , Rui Wang , Xianfang Zeng , Gang Yu , Hai-Bao Chen

Text-To-Image (TTI) models, such as DALL-E and StableDiffusion, have demonstrated remarkable prompt-based image generation capabilities. Multilingual encoders may have a substantial impact on the cultural agency of these models, as language…

Computation and Language · Computer Science 2024-08-14 Mor Ventura , Eyal Ben-David , Anna Korhonen , Roi Reichart