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Current diffusion models create photorealistic images given a text prompt as input but struggle to correctly bind attributes mentioned in the text to the right objects in the image. This is evidenced by our novel image-graph alignment model…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Maria Mihaela Trusca , Wolf Nuyts , Jonathan Thomm , Robert Honig , Thomas Hofmann , Tinne Tuytelaars , Marie-Francine Moens

While Text-to-Image (T2I) diffusion models excel at generating visually appealing images of individual instances, they struggle to accurately position and control the features generation of multiple instances. The Layout-to-Image (L2I) task…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Yinwei Wu , Xianpan Zhou , Bing Ma , Xuefeng Su , Kai Ma , Xinchao Wang

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

Text-to-Image (T2I) diffusion models have shown impressive results in generating visually compelling images following user prompts. Building on this, various methods further fine-tune the pre-trained T2I model for specific tasks. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-24 Tsu-Jui Fu , Yusu Qian , Chen Chen , Wenze Hu , Zhe Gan , Yinfei Yang

We demonstrate text as a strong cross-modal interface. Rather than relying on deep embeddings to connect image and language as the interface representation, our approach represents an image as text, from which we enjoy the interpretability…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Chen Wei , Chenxi Liu , Siyuan Qiao , Zhishuai Zhang , Alan Yuille , Jiahui Yu

Existing approaches for controlling text-to-image diffusion models, while powerful, do not allow for explicit 3D object-centric control, such as precise control of object orientation. In this work, we address the problem of multi-object…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Rishubh Parihar , Vaibhav Agrawal , Sachidanand VS , R. Venkatesh Babu

We propose EditCrafter, a high-resolution image editing method that operates without tuning, leveraging pretrained text-to-image (T2I) diffusion models to process images at resolutions significantly exceeding those used during training.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Kunho Kim , Sumin Seo , Yongjun Cho , Hyungjin Chung

Recently, Text-to-Image (T2I) synthesis technology has made tremendous strides. Numerous representative T2I models have emerged and achieved promising application outcomes, such as DALL-E, Stable Diffusion, Imagen, etc. In practice, it has…

Cryptography and Security · Computer Science 2025-09-24 Wenbo Jiang , Jiaming He , Hongwei Li , Rui Zhang , Hanxiao Chen , Meng Hao , Haomiao Yang , Qingchuan Zhao , Guowen Xu

Precise image editing with text-to-image models has attracted increasing interest due to their remarkable generative capabilities and user-friendly nature. However, such attempts face the pivotal challenge of misalignment between the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Wei Wu , Qingnan Fan , Shuai Qin , Hong Gu , Ruoyu Zhao , Antoni B. Chan

\textit{Nature is infinitely resolution-free}. In the context of this reality, existing diffusion models, such as Diffusion Transformers, often face challenges when processing image resolutions outside of their trained domain. To address…

Machine Learning · Computer Science 2024-10-21 ZiDong Wang , Zeyu Lu , Di Huang , Cai Zhou , Wanli Ouyang , and Lei Bai

Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing high-fidelity, diverse, and visually realistic images from textual prompts. Despite these advances, existing models struggle with complex prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Eric Hanchen Jiang , Yasi Zhang , Zhi Zhang , Yixin Wan , Andrew Lizarraga , Shufan Li , Ying Nian Wu

Diffusion models excel in many generative modeling tasks, notably in creating images from text prompts, a task referred to as text-to-image (T2I) generation. Despite the ability to generate high-quality images, these models often replicate…

Multimedia · Computer Science 2024-02-20 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Haonan Wang , Kenji Kawaguchi

Diffusion models, such as Stable Diffusion, have shown incredible performance on text-to-image generation. Since text-to-image generation often requires models to generate visual concepts with fine-grained details and attributes specified…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Xuehai He , Weixi Feng , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , William Yang Wang , Xin Eric Wang

Visual generation grounded in Visual Foundation Model (VFM) representations offers a highly promising unified pathway for integrating visual understanding, perception, and generation. Despite this potential, training large-scale…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Minglei Shi , Haolin Wang , Borui Zhang , Wenzhao Zheng , Bohan Zeng , Ziyang Yuan , Xiaoshi Wu , Yuanxing Zhang , Huan Yang , Xintao Wang , Pengfei Wan , Kun Gai , Jie Zhou , Jiwen Lu

Latent Diffusion Models (LDMs) are renowned for their powerful capabilities in image and video synthesis. Yet, compared to text-to-image (T2I) editing, text-to-video (T2V) editing suffers from a lack of decent temporal consistency and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Tianyi Lu , Xing Zhang , Jiaxi Gu , Renjing Pei , Songcen Xu , Xingjun Ma , Hang Xu , Zuxuan Wu

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai

Controllable pathology image synthesis requires reliable regulation of spatial layout, tissue morphology, and semantic detail. However, existing text-guided diffusion models offer only coarse global control and lack the ability to enforce…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yuntao Shou , Xiangyong Cao , Qian Zhao , Deyu Meng

Text-guided image-to-image diffusion models excel in translating images based on textual prompts, allowing for precise and creative visual modifications. However, such a powerful technique can be misused for spreading misinformation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Wenhao Wang , Yifan Sun , Zongxin Yang , Zhentao Tan , Zhengdong Hu , Yi Yang

Diffusion bridges have shown potential in paired image-to-image (I2I) translation tasks. However, existing methods are limited by their unidirectional nature, requiring separate models for forward and reverse translations. This not only…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Duc Kieu , Kien Do , Toan Nguyen , Dang Nguyen , Thin Nguyen

Personalized text-to-image (T2I) synthesis based on diffusion models has attracted significant attention in recent research. However, existing methods primarily concentrate on customizing subjects or styles, neglecting the exploration of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Hai Wang , Xiaoyu Xiang , Yuchen Fan , Jing-Hao Xue