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Related papers: Lay2Story: Extending Diffusion Transformers for La…

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In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

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

Training-free consistent text-to-image generation depicting the same subjects across different images is a topic of widespread recent interest. Existing works in this direction predominantly rely on cross-frame self-attention; which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Jaskirat Singh , Junshen Kevin Chen , Jonas Kohler , Michael Cohen

Recent advancements in text-to-image (T2I) generative models have shown remarkable capabilities in producing diverse and imaginative visuals based on text prompts. Despite the advancement, these diffusion models sometimes struggle to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xiaohui Chen , Yongfei Liu , Yingxiang Yang , Jianbo Yuan , Quanzeng You , Li-Ping Liu , Hongxia Yang

Layout generation is a foundation task of graphic design, which requires the integration of visual aesthetics and harmonious expression of content delivery. However, existing methods still face challenges in generating precise and visually…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yu Li , Yifan Chen , Gongye Liu , Fei Yin , Qingyan Bai , Jie Wu , Hongfa Wang , Ruihang Chu , Yujiu Yang

With the development of diffusion models, enhancing spatial controllability in text-to-image generation has become a vital challenge. As a representative task for addressing this challenge, layout-to-image generation aims to generate images…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Sida Huang , Siqi Huang , Ping Luo , Hongyuan Zhang

Text-to-story visualization is challenging due to the need for consistent interaction among multiple characters across frames. Existing methods struggle with character consistency, leading to artifact generation and inaccurate dialogue…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Ayan Banerjee , Josep Llados , Umapada Pal , Anjan Dutta

For recent diffusion-based generative models, maintaining consistent content across a series of generated images, especially those containing subjects and complex details, presents a significant challenge. In this paper, we propose a new…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yupeng Zhou , Daquan Zhou , Ming-Ming Cheng , Jiashi Feng , Qibin Hou

We present Story2Board, a training-free framework for expressive storyboard generation from natural language. Existing methods narrowly focus on subject identity, overlooking key aspects of visual storytelling such as spatial composition,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 David Dinkevich , Matan Levy , Omri Avrahami , Dvir Samuel , Dani Lischinski

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

Thanks to the rapid development of diffusion models, unprecedented progress has been witnessed in image synthesis. Prior works mostly rely on pre-trained linguistic models, but a text is often too abstract to properly specify all the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Binbin Yang , Yi Luo , Ziliang Chen , Guangrun Wang , Xiaodan Liang , Liang Lin

Diffusion models developed on top of powerful text-to-image generation models like Stable Diffusion achieve remarkable success in visual story generation. However, the best-performing approach considers historically generated results as…

Computer Vision and Pattern Recognition · Computer Science 2023-05-29 Zhangyin Feng , Yuchen Ren , Xinmiao Yu , Xiaocheng Feng , Duyu Tang , Shuming Shi , Bing Qin

Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Guangcong Zheng , Xianpan Zhou , Xuewei Li , Zhongang Qi , Ying Shan , Xi Li

Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Long Lian , Boyi Li , Adam Yala , Trevor Darrell

Diffusion models have demonstrated remarkable capabilities in generating high-quality images. Recent advancements in Layout-to-Image (L2I) generation have leveraged positional conditions and textual descriptions to facilitate precise and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Qiang Xiang , Shuang Sun , Binglei Li , Dejia Song , Huaxia Li , Nemo Chen , Xu Tang , Yao Hu , Junping Zhang

Compositional text-to-video generation, which requires synthesizing dynamic scenes with multiple interacting entities and precise spatial-temporal relationships, remains a critical challenge for diffusion-based models. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Weijie He , Mushui Liu , Yunlong Yu , Zhao Wang , Chao Wu

Diffusion models have been recognized for their ability to generate images that are not only visually appealing but also of high artistic quality. As a result, Layout-to-Image (L2I) generation has been proposed to leverage region-specific…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Hui Zhang , Dexiang Hong , Yitong Wang , Jie Shao , Xinglong Wu , Zuxuan Wu , Yu-Gang Jiang

Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling. Existing approaches to this problem…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tao Liu , Kai Wang , Senmao Li , Joost van de Weijer , Fahad Shahbaz Khan , Shiqi Yang , Yaxing Wang , Jian Yang , Ming-Ming Cheng

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

Visual storytelling with diffusion models has made impressive strides in maintaining character consistency across narrative scenes. However, a critical gap remains: while these methods ensure a character remains consistent across scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Manogna Sreenivas , Rohit Kumar , Soma Biswas
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