English
Related papers

Related papers: DreamSync: Aligning Text-to-Image Generation with …

200 papers

Current text-to-image (T2I) benchmarks evaluate models on rigid prompts, potentially underestimating true generative capabilities due to prompt sensitivity and creating biases that favor certain models while disadvantaging others. We…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Haosheng Gan , Berk Tinaz , Mohammad Shahab Sepehri , Zalan Fabian , Mahdi Soltanolkotabi

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

Unified multimodal understanding and generation models recently have achieve significant improvement in image generation capability, yet a large gap remains in instruction following and detail preservation compared to systems that tightly…

Text-to-image (T2I) diffusion models, when fine-tuned on a few personal images, can generate visuals with a high degree of consistency. However, such fine-tuned models are not robust; they often fail to compose with concepts of pretrained…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Kyungmin Lee , Sangkyung Kwak , Kihyuk Sohn , Jinwoo Shin

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

The recent advancements in text-to-image generative models have been remarkable. Yet, the field suffers from a lack of evaluation metrics that accurately reflect the performance of these models, particularly lacking fine-grained metrics…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Zhiyu Tan , Xiaomeng Yang , Luozheng Qin , Mengping Yang , Cheng Zhang , Hao Li

Large-scale generative models have shown impressive image-generation capabilities, propelled by massive data. However, this often inadvertently leads to the generation of harmful or inappropriate content and raises copyright concerns.…

Machine Learning · Computer Science 2025-03-11 Myeongseob Ko , Henry Li , Zhun Wang , Jonathan Patsenker , Jiachen T. Wang , Qinbin Li , Ming Jin , Dawn Song , Ruoxi Jia

With the rapid advancement of large multimodal models (LMMs), recent text-to-image (T2I) models can generate high-quality images and demonstrate great alignment to short prompts. However, they still struggle to effectively understand and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Juntong Wang , Huiyu Duan , Jiarui Wang , Ziheng Jia , Guangtao Zhai , Xiongkuo Min

Current vision-language generative models rely on expansive corpora of paired image-text data to attain optimal performance and generalization capabilities. However, automatically collecting such data (e.g. via large-scale web scraping)…

Computer Vision and Pattern Recognition · Computer Science 2023-10-06 Tianhong Li , Sangnie Bhardwaj , Yonglong Tian , Han Zhang , Jarred Barber , Dina Katabi , Guillaume Lajoie , Huiwen Chang , Dilip Krishnan

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

Scaling up model and data size has been quite successful for the evolution of LLMs. However, the scaling law for the diffusion based text-to-image (T2I) models is not fully explored. It is also unclear how to efficiently scale the model for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Hao Li , Yang Zou , Ying Wang , Orchid Majumder , Yusheng Xie , R. Manmatha , Ashwin Swaminathan , Zhuowen Tu , Stefano Ermon , Stefano Soatto

Recent advancements in Text-to-Image (T2I) diffusion models have demonstrated impressive success in generating high-quality images with zero-shot generalization capabilities. Yet, current models struggle to closely adhere to prompt…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Hyun Kang , Dohae Lee , Myungjin Shin , In-Kwon Lee

Text-to-image diffusion models have shown impressive capabilities in generating realistic visuals from natural-language prompts, yet they often struggle with accurately binding attributes to corresponding objects, especially in prompts…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Do Huu Dat , Nam Hyeonu , Po-Yuan Mao , Tae-Hyun Oh

Recent progress in text-to-image (T2I) diffusion models (DMs) has enabled high-quality visual synthesis from diverse textual prompts. Yet, most existing T2I DMs, even those equipped with large language model (LLM)-based text encoders,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Siqi Kou , Jiachun Jin , Zetong Zhou , Ye Ma , Yugang Wang , Quan Chen , Peng Jiang , Xiao Yang , Jun Zhu , Kai Yu , Zhijie Deng

Text-to-image (T2I) diffusion models have drawn attention for their ability to generate high-quality images with precise text alignment. However, these models can also be misused to produce inappropriate content. Existing safety measures,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Hongxiang Zhang , Yifeng He , Hao Chen

In recent times, the focus on text-to-audio (TTA) generation has intensified, as researchers strive to synthesize audio from textual descriptions. However, most existing methods, though leveraging latent diffusion models to learn the…

Sound · Computer Science 2024-03-14 Shentong Mo , Jing Shi , Yapeng Tian

Large-scale text-to-image diffusion models have been a ground-breaking development in generating convincing images following an input text prompt. The goal of image editing research is to give users control over the generated images by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Chuanming Tang , Kai Wang , Joost van de Weijer

Artificial Intelligence-Generated Content (AIGC) has made significant strides, with high-resolution text-to-image (T2I) generation becoming increasingly critical for improving users' Quality of Experience (QoE). Although…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Chongbin Yi , Yuxin Liang , Ziqi Zhou , Peng Yang

Text-to-Image (T2I) models have transformed visual content creation, producing highly realistic images from natural language prompts. However, concerns persist around their potential to replicate and magnify existing societal biases. To…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Sedat Porikli , Vedat Porikli

The rapid development of diffusion models has triggered diverse applications. Identity-preserving text-to-image generation (ID-T2I) particularly has received significant attention due to its wide range of application scenarios like AI…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Weifeng Chen , Jiacheng Zhang , Jie Wu , Hefeng Wu , Xuefeng Xiao , Liang Lin