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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

Generative AI models, particularly Text-to-Video (T2V) systems, offer a promising avenue for transforming science education by automating the creation of engaging and intuitive visual explanations. In this work, we take a first step toward…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Megha Mariam K. M , Aditya Arun , Zakaria Laskar , C. V. Jawahar

Recent text-to-image (T2I) generation models have advanced significantly, enabling the creation of high-fidelity images from textual prompts. However, existing evaluation benchmarks primarily focus on the explicit alignment between…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Wenchao Zhang , Jiahe Tian , Runze He , Jizhong Han , Jiao Dai , Miaomiao Feng , Wei Mi , Xiaodan Zhang

Text-to-image (T2I) models have achieved remarkable progress, yet they continue to struggle with complex prompts that require simultaneously handling multiple objects, relations, and attributes. Existing inference-time strategies, such as…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Shantanu Jaiswal , Mihir Prabhudesai , Nikash Bhardwaj , Zheyang Qin , Amir Zadeh , Chuan Li , Katerina Fragkiadaki , Deepak Pathak

Rectified Flow (RF) models trained with a Flow matching framework have achieved state-of-the-art performance on Text-to-Image (T2I) conditional generation. Yet, multiple benchmarks show that synthetic images can still suffer from poor…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Chao Wang , Giulio Franzese , Alessandro Finamore , Pietro Michiardi

Text-to-image (T2I) models have recently experienced rapid development, achieving astonishing performance in terms of fidelity and textual alignment capabilities. However, given a long paragraph (up to 512 words), these generation models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Weijia Wu , Zhuang Li , Yefei He , Mike Zheng Shou , Chunhua Shen , Lele Cheng , Yan Li , Tingting Gao , Di Zhang

Image-text retrieval, as a fundamental and important branch of information retrieval, has attracted extensive research attentions. The main challenge of this task is cross-modal semantic understanding and matching. Some recent works focus…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Weijing Chen , Linli Yao , Qin Jin

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

Text-to-image (T2I) generation has seen significant progress with diffusion models, enabling generation of photo-realistic images from text prompts. Despite this progress, existing methods still face challenges in following complex text…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Ashish Goswami , Satyam Kumar Modi , Santhosh Rishi Deshineni , Harman Singh , Prathosh A. P , Parag Singla

Despite thousands of researchers, engineers, and artists actively working on improving text-to-image generation models, systems often fail to produce images that accurately align with the text inputs. We introduce TIFA (Text-to-Image…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yushi Hu , Benlin Liu , Jungo Kasai , Yizhong Wang , Mari Ostendorf , Ranjay Krishna , Noah A Smith

Despite the remarkable capabilities of text-to-image (T2I) generation models, real-world applications often demand fine-grained, iterative image editing that existing methods struggle to provide. Key challenges include granular instruction…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Zihan Liang , Jiahao Sun , Haoran Ma

This paper explores the feasibility of using text-to-image models in a zero-shot setup to generate images for taxonomy concepts. While text-based methods for taxonomy enrichment are well-established, the potential of the visual dimension…

Computation and Language · Computer Science 2025-03-14 Viktor Moskvoretskii , Alina Lobanova , Ekaterina Neminova , Chris Biemann , Alexander Panchenko , Irina Nikishina

The rapid advancements of Text-to-Image (T2I) models have ushered in a new phase of AI-generated content, marked by their growing ability to interpret and follow user instructions. However, existing T2I model evaluation benchmarks fall…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Xinyu Wei , Jinrui Zhang , Zeqing Wang , Hongyang Wei , Zhen Guo , Lei Zhang

Despite recent advances in text-to-image (T2I) models, they often fail to faithfully render all elements of complex prompts, frequently omitting or misrepresenting specific objects and attributes. Test-time optimization has emerged as a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Mohammad Hossein Sameti , Amir M. Mansourian , Arash Marioriyad , Soheil Fadaee Oshyani , Mohammad Hossein Rohban , Mahdieh Soleymani Baghshah

With the evolution of Text-to-Image (T2I) models, the quality defects of AI-Generated Images (AIGIs) pose a significant barrier to their widespread adoption. In terms of both perception and alignment, existing models cannot always guarantee…

Text-to-image (T2I) synthesis has recently achieved significant advancements. However, challenges remain in the model's compositionality, which is the ability to create new combinations from known components. We introduce Winoground-T2I, a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Xiangru Zhu , Penglei Sun , Chengyu Wang , Jingping Liu , Zhixu Li , Yanghua Xiao , Jun Huang

Generative diffusion models are developing rapidly and attracting increasing attention due to their wide range of applications. Image-to-Video (I2V) generation has become a major focus in the field of video synthesis. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Ailing Zhang , Lina Lei , Dehong Kong , Zhixin Wang , Jiaqi Xu , Fenglong Song , Chun-Le Guo , Chang Liu , Fan Li , Jie Chen

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhicai Wang , Longhui Wei , Tan Wang , Heyu Chen , Yanbin Hao , Xiang Wang , Xiangnan He , Qi Tian

Text-to-Image (T2I) generative models have revolutionized content creation but remain highly sensitive to prompt phrasing, often requiring users to repeatedly refine prompts multiple times without clear feedback. While techniques such as…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Chieh-Yun Chen , Min Shi , Gong Zhang , Humphrey Shi

Despite remarkable progress in Text-to-Image models, many real-world applications require generating coherent image sets with diverse consistency requirements. Existing consistent methods often focus on a specific domain with specific…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Chengyou Jia , Xin Shen , Zhuohang Dang , Zhuohang Dang , Changliang Xia , Weijia Wu , Xinyu Zhang , Hangwei Qian , Ivor W. Tsang , Minnan Luo
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