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This paper introduces innovative solutions to enhance spatial controllability in diffusion models reliant on text queries. We first introduce vision guidance as a foundational spatial cue within the perturbed distribution. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zipeng Qi , Guoxi Huang , Chenyang Liu , Fei Ye

We seek to give users precise control over diffusion-based image generation by modeling complex scenes as sequences of layers, which define the desired spatial arrangement and visual attributes of objects in the scene. Collage Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Vishnu Sarukkai , Linden Li , Arden Ma , Christopher Ré , Kayvon Fatahalian

While modern diffusion models excel at generating high-quality and diverse images, they still struggle with high-fidelity compositional and multimodal control, particularly when users simultaneously specify text prompts, subject references,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yusuf Dalva , Guocheng Gordon Qian , Maya Goldenberg , Tsai-Shien Chen , Kfir Aberman , Sergey Tulyakov , Pinar Yanardag , Kuan-Chieh Jackson Wang

Controllable layout generation refers to the process of creating a plausible visual arrangement of elements within a graphic design (e.g., document and web designs) with constraints representing design intentions. Although recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Jian Chen , Ruiyi Zhang , Yufan Zhou , Rajiv Jain , Zhiqiang Xu , Ryan Rossi , Changyou Chen

Diffusion models have significantly advanced text-to-image generation, laying the foundation for the development of personalized generative frameworks. However, existing methods lack precise layout controllability and overlook the potential…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Wei Li , Hebei Li , Yansong Peng , Siying Wu , Yueyi Zhang , Xiaoyan Sun

We propose a diffusion-based approach for Text-to-Image (T2I) generation with consistent and interactive 3D layout control and editing. While prior methods improve spatial adherence using 2D cues or iterative copy-warp-paste strategies,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Andrea Rigo , Luca Stornaiuolo , Weijie Wang , Mauro Martino , Bruno Lepri , Nicu Sebe

Diffusion models have revolutionized image generation, yet several challenges restrict their application to large-image domains, such as digital pathology and satellite imagery. Given that it is infeasible to directly train a model on…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Srikar Yellapragada , Alexandros Graikos , Kostas Triaridis , Prateek Prasanna , Rajarsi R. Gupta , Joel Saltz , Dimitris Samaras

Diffusion models have attracted significant attention due to the remarkable ability to create content and generate data for tasks like image classification. However, the usage of diffusion models to generate the high-quality object…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Kai Chen , Enze Xie , Zhe Chen , Yibo Wang , Lanqing Hong , Zhenguo Li , Dit-Yan Yeung

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka

Diffusion models are a powerful class of generative models capable of producing high-quality images from pure noise using a simple text prompt. While most methods which introduce additional spatial constraints into the generated images…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Zakaria Patel , Kirill Serkh

Diffusion methods have been proven to be very effective to generate images while conditioning on a text prompt. However, and although the quality of the generated images is unprecedented, these methods seem to struggle when trying to…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Álvaro Barbero Jiménez

Text-to-image (T2I) generative diffusion models have demonstrated outstanding performance in synthesizing diverse, high-quality visuals from text captions. Several layout-to-image models have been developed to control the generation process…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Ahmad Süleyman , Göksel Biricik

Existing text-to-image diffusion models struggle to synthesize realistic images given dense captions, where each text prompt provides a detailed description for a specific image region. To address this, we propose DenseDiffusion, a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-25 Yunji Kim , Jiyoung Lee , Jin-Hwa Kim , Jung-Woo Ha , Jun-Yan Zhu

Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generated images with respect to the text description, such as…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Qiucheng Wu , Yujian Liu , Handong Zhao , Trung Bui , Zhe Lin , Yang Zhang , Shiyu Chang

Recent advancements in large-scale text-to-image diffusion models have enabled many applications in image editing. However, none of these methods have been able to edit the layout of single existing images. To address this gap, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-06-23 Zhiyuan Zhang , Zhitong Huang , Jing Liao

Diffusion models have recently gained recognition for generating diverse and high-quality content, especially in image synthesis. These models excel not only in creating fixed-size images but also in producing panoramic images. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiaoyu Zhang , Teng Zhou , Xinlong Zhang , Jia Wei , Yongchuan Tang

Poster layout is a crucial aspect of poster design. Prior methods primarily focus on the correlation between visual content and graphic elements. However, a pleasant layout should also consider the relationship between visual and textual…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Fengheng Li , An Liu , Wei Feng , Honghe Zhu , Yaoyu Li , Zheng Zhang , Jingjing Lv , Xin Zhu , Junjie Shen , Zhangang Lin , Jingping Shao

Transparent image layer generation plays a significant role in digital art and design workflows. Existing methods typically decompose transparent layers from a single RGB image using a set of tools or generate multiple transparent layers…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Dingbang Huang , Wenbo Li , Yifei Zhao , Xinyu Pan , Chun Wang , Yanhong Zeng , Bo Dai

Generative image editing has recently witnessed extremely fast-paced growth. Some works use high-level conditioning such as text, while others use low-level conditioning. Nevertheless, most of them lack fine-grained control over the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Vidit Goel , Elia Peruzzo , Yifan Jiang , Dejia Xu , Xingqian Xu , Nicu Sebe , Trevor Darrell , Zhangyang Wang , Humphrey Shi