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Text-to-Image (T2I) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased. Existing safety methods typically refine prompts using…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Jinwoo Jeon , JunHyeok Oh , Hayeong Lee , Byung-Jun Lee

With advances in the quality of text-to-image (T2I) models has come interest in benchmarking their prompt faithfulness -- the semantic coherence of generated images to the prompts they were conditioned on. A variety of T2I faithfulness…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Michael Saxon , Fatima Jahara , Mahsa Khoshnoodi , Yujie Lu , Aditya Sharma , William Yang Wang

Text-to-Image (T2I) generation has made significant advancements with diffusion models, yet challenges persist in handling complex instructions, ensuring fine-grained content control, and maintaining deep semantic consistency. Existing T2I…

Machine Learning · Computer Science 2025-08-08 Xiaoqi Dong , Xiangyu Zhou , Nicholas Evans , Yujia Lin

Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic images. Despite the progress, these models still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Oscar Mañas , Pietro Astolfi , Melissa Hall , Candace Ross , Jack Urbanek , Adina Williams , Aishwarya Agrawal , Adriana Romero-Soriano , Michal Drozdzal

Progress in Text-to-Image (T2I) models has significantly improved the generation of images from textual descriptions. However, existing evaluation metrics do not adequately assess the models' ability to handle a diverse range of textual…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Jingtao Cao , Zheng Zhang , Hongru Wang , Kam-Fai Wong

The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on static datasets, motivating researchers to seek alternative ways to evaluate the T2I progress. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Jiahui Chen , Candace Ross , Reyhane Askari-Hemmat , Koustuv Sinha , Melissa Hall , Michal Drozdzal , Adriana Romero-Soriano

Contemporary Text-to-Image (T2I) models frequently depend on qualitative human evaluations to assess the consistency between synthesized images and the text prompts. There is a demand for quantitative and automatic evaluation tools, given…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ziyuan Qin , Dongjie Cheng , Haoyu Wang , Huahui Yi , Yuting Shao , Zhiyuan Fan , Kang Li , Qicheng Lao

Large Vision-Language Models (VLMs) are increasingly used to evaluate outputs of other models, for image-to-text (I2T) tasks such as visual question answering, and text-to-image (T2I) generation tasks. Despite this growing reliance, the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Mohammed Safi Ur Rahman Khan , Sanjay Suryanarayanan , Tushar Anand , Mitesh M. Khapra

Recent advances in text-to-image (T2I) models, especially diffusion-based architectures, have significantly improved the visual quality of generated images. However, these models continue to struggle with a critical limitation: maintaining…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Yifan Shen , Yangyang Shu , Hye-young Paik , Yulei Sui

Text-to-image (T2I) generation models have made significant strides but still struggle with prompt sensitivity: even minor changes in prompt wording can yield inconsistent or inaccurate outputs. To address this challenge, we introduce a…

Machine Learning · Computer Science 2025-07-31 Mohammad Abdul Hafeez Khan , Yash Jain , Siddhartha Bhattacharyya , Vibhav Vineet

Although recent text-to-image generative models have achieved impressive performance, they still often struggle with capturing the compositional complexities of prompts including attribute binding, and spatial relationships between…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Seyed Mohammad Hadi Hosseini , Amir Mohammad Izadi , Ali Abdollahi , Armin Saghafian , Mahdieh Soleymani Baghshah

Text-to-Image (T2I) models have recently achieved remarkable success in generating images from textual descriptions. However, challenges still persist in accurately rendering complex scenes where actions and interactions form the primary…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Vatsal Malaviya , Agneet Chatterjee , Maitreya Patel , Yezhou Yang , Chitta Baral

As large language models have demonstrated impressive performance in many domains, recent works have adopted language models (LMs) as controllers of visual modules for vision-and-language tasks. While existing work focuses on equipping LMs…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Jaemin Cho , Abhay Zala , Mohit Bansal

Recently, Text-to-Image (T2I) generation models have achieved significant advancements. Correspondingly, many automated metrics have emerged to evaluate the image-text alignment capabilities of generative models. However, the performance…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Shuhao Han , Haotian Fan , Jiachen Fu , Liang Li , Tao Li , Junhui Cui , Yunqiu Wang , Yang Tai , Jingwei Sun , Chunle Guo , Chongyi Li

In text-to-image (T2I) generation, a prevalent training technique involves utilizing Vision Language Models (VLMs) for image re-captioning. Even though VLMs are known to exhibit hallucination, generating descriptive content that deviates…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Weichen Yu , Ziyan Yang , Shanchuan Lin , Qi Zhao , Jianyi Wang , Liangke Gui , Matt Fredrikson , Lu Jiang

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

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

Text-to-image (T2I) models such as Stable Diffusion have advanced rapidly and are now widely used in content creation. However, these models can be misused to generate harmful content, including nudity or violence, posing significant safety…

Cryptography and Security · Computer Science 2025-06-13 Zilong Wang , Xiang Zheng , Xiaosen Wang , Bo Wang , Xingjun Ma , Yu-Gang Jiang

While recent text-to-image (T2I) models show impressive capabilities in synthesizing images from brief descriptions, their performance significantly degrades when confronted with long, detail-intensive prompts required in professional…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Qirui Jiao , Daoyuan Chen , Yilun Huang , Xika Lin , Ying Shen , Yaliang Li

Text-to-image models are powerful for producing high-quality images based on given text prompts, but crafting these prompts often requires specialized vocabulary. To address this, existing methods train rewriting models with supervision…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Hongji Yang , Yucheng Zhou , Wencheng Han , Jianbing Shen
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