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Over the past few years, Text-to-Image (T2I) generation approaches based on diffusion models have gained significant attention. However, vanilla diffusion models often suffer from spelling inaccuracies in the text displayed within the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Sanyam Lakhanpal , Shivang Chopra , Vinija Jain , Aman Chadha , Man Luo

Text-to-image generative models have achieved remarkable visual quality but still struggle with compositionality$-$accurately capturing object relationships, attribute bindings, and fine-grained details in prompts. A key limitation is that…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Arman Zarei , Jiacheng Pan , Matthew Gwilliam , Soheil Feizi , Zhenheng Yang

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

Text-to-image generative models excel in creating images from text but struggle with ensuring alignment and consistency between outputs and prompts. This paper introduces TextMatch, a novel framework that leverages multimodal optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Yucong Luo , Mingyue Cheng , Jie Ouyang , Xiaoyu Tao , Qi Liu

Rapid advances in text-to-image (T2I) generation have raised higher requirements for evaluation methodologies. Existing benchmarks center on objective capabilities and dimensions, but lack an application-scenario perspective, limiting…

Artificial Intelligence · Computer Science 2025-09-23 Xiaojing Dong , Weilin Huang , Liang Li , Yiying Li , Shu Liu , Tongtong Ou , Shuang Ouyang , Yu Tian , Fengxuan Zhao

We provide a new multi-task benchmark for evaluating text-to-image models. We perform a human evaluation comparing the most common open-source (Stable Diffusion) and commercial (DALL-E 2) models. Twenty computer science AI graduate students…

Real-world design tasks - such as picture book creation, film storyboard development using character sets, photo retouching, visual effects, and font transfer - are highly diverse and complex, requiring deep interpretation and extraction of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Chen Liang , Lianghua Huang , Jingwu Fang , Huanzhang Dou , Wei Wang , Zhi-Fan Wu , Yupeng Shi , Junge Zhang , Xin Zhao , Yu Liu

One challenge in text-to-image (T2I) generation is the inadvertent reflection of culture gaps present in the training data, which signifies the disparity in generated image quality when the cultural elements of the input text are rarely…

Computer Vision and Pattern Recognition · Computer Science 2023-07-07 Bingshuai Liu , Longyue Wang , Chenyang Lyu , Yong Zhang , Jinsong Su , Shuming Shi , Zhaopeng Tu

Text-to-Image (T2I) generation has long been an open problem, with compositional synthesis remaining particularly challenging. This task requires accurate rendering of complex scenes containing multiple objects that exhibit diverse…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Shijian Wang , Runhao Fu , Siyi Zhao , Qingqin Zhan , Xingjian Wang , Jiarui Jin , Yuan Lu , Hanqian Wu , Cunjian Chen

Image editing aims to edit the given synthetic or real image to meet the specific requirements from users. It is widely studied in recent years as a promising and challenging field of Artificial Intelligence Generative Content (AIGC).…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Xincheng Shuai , Henghui Ding , Xingjun Ma , Rongcheng Tu , Yu-Gang Jiang , Dacheng Tao

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

Recent advancements in text-to-image (T2I) generation models have transformed the field. However, challenges persist in generating images that reflect demanding textual descriptions, especially for fine-grained details and unusual…

Multimedia · Computer Science 2025-02-21 Ran Li , Xiaomeng Jin , Heng ji

Text-to-image models have shown remarkable progress in generating high-quality images from user-provided prompts. Despite this, the quality of these images varies due to the models' sensitivity to human language nuances. With advancements…

Artificial Intelligence · Computer Science 2024-06-14 Xinrui Yang , Zhuohan Wang , Anthony Hu

Text-to-image (T2I) generation has achieved remarkable progress in instruction following and aesthetics. However, a persistent challenge is the prevalence of physical artifacts, such as anatomical and structural flaws, which severely…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Jia Wang , Jie Hu , Xiaoqi Ma , Hanghang Ma , Yanbing Zeng , Xiaoming Wei

Recent advances in Text-to-3D (T23D) generative models have enabled the synthesis of diverse, high-fidelity 3D assets from textual prompts. However, existing challenges restrict the development of reliable T23D quality assessment (T23DQA).…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Bingyang Cui , Yujie Zhang , Qi Yang , Zhu Li , Yiling Xu

Recent advances in text-to-image (T2I) generation have led to impressive visual results. However, these models still face significant challenges when handling complex prompt, particularly those involving multiple subjects with distinct…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Lifeng Chen , Jiner Wang , Zihao Pan , Beier Zhu , Xiaofeng Yang , Chi Zhang

Text-to-image (T2I) models are capable of generating visually impressive images, yet they often fail to accurately capture specific attributes in user prompts, such as the correct number of objects with the specified colors. The diversity…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Kevin David Hayes , Micah Goldblum , Vikash Sehwag , Gowthami Somepalli , Ashwinee Panda , Tom Goldstein

The burgeoning field of Artificial Intelligence Generated Content (AIGC) is witnessing rapid advancements, particularly in video generation. This paper introduces AIGCBench, a pioneering comprehensive and scalable benchmark designed to…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Fanda Fan , Chunjie Luo , Wanling Gao , Jianfeng Zhan

Infographics are composite visual artifacts that combine data visualizations with textual and illustrative elements to communicate information. While recent text-to-image (T2I) models can generate aesthetically appealing images, their…

Recent breakthroughs in large multimodal models (LMMs) have significantly advanced both text-to-image (T2I) generation and image-to-text (I2T) interpretation. However, many generated images still suffer from issues related to perceptual…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Jiarui Wang , Huiyu Duan , Yu Zhao , Juntong Wang , Guangtao Zhai , Xiongkuo Min