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Related papers: Using Text-to-Image Generation for Architectural D…

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In this paper, we focus on generating realistic images from text descriptions. Current methods first generate an initial image with rough shape and color, and then refine the initial image to a high-resolution one. Most existing…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Minfeng Zhu , Pingbo Pan , Wei Chen , Yi Yang

Text-to-image generation models have achieved strong performance in culturally homogeneous settings, yet their ability to generate multicultural scenes, where people and landmarks originate from different cultures, remains largely…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Parth Bhalerao , Mounika Yalamarty , Brian Trinh , Oana Ignat

Large-scale Text-to-image Generation Models (LTGMs) (e.g., DALL-E), self-supervised deep learning models trained on a huge dataset, have demonstrated the capacity for generating high-quality open-domain images from multi-modal input.…

Human-Computer Interaction · Computer Science 2023-02-17 Hyung-Kwon Ko , Gwanmo Park , Hyeon Jeon , Jaemin Jo , Juho Kim , Jinwook Seo

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…

Recent advancements in artificial intelligence, such as computer vision and deep learning, have led to the emergence of numerous generative AI platforms, particularly for image generation. However, the application of AI-generated image…

Human-Computer Interaction · Computer Science 2024-06-21 Yuying Tang , Mariana Ciancia , Zhigang Wang , Ze Gao

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Text-to-image (TTI) diffusion models have demonstrated impressive results in generating high-resolution images of complex and imaginative scenes. Recent approaches have further extended these methods with personalization techniques that…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Tanzila Rahman , Shweta Mahajan , Hsin-Ying Lee , Jian Ren , Sergey Tulyakov , Leonid Sigal

Recent advances in text-to-image diffusion models have enabled the photorealistic generation of images from text prompts. Despite the great progress, existing models still struggle to generate compositional multi-concept images naturally,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Hazarapet Tunanyan , Dejia Xu , Shant Navasardyan , Zhangyang Wang , Humphrey Shi

Text-to-image models are enabling efficient design space exploration, rapidly generating images from text prompts. However, many generative AI tools are imperfect for product design applications as they are not built for the goals and…

Human-Computer Interaction · Computer Science 2025-01-22 Leah Chong , I-Ping Lo , Jude Rayan , Steven Dow , Faez Ahmed , Ioanna Lykourentzou

The landscape of image generation has rapidly evolved, from early GAN-based approaches to diffusion models and, most recently, to unified generative architectures that seek to bridge understanding and generation tasks. Recent advances,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Sixiang Chen , Jinbin Bai , Zhuoran Zhao , Tian Ye , Qingyu Shi , Donghao Zhou , Wenhao Chai , Xin Lin , Jianzong Wu , Chao Tang , Shilin Xu , Tao Zhang , Haobo Yuan , Yikang Zhou , Wei Chow , Linfeng Li , Xiangtai Li , Lei Zhu , Lu Qi

Text-to-image diffusion models have been adopted into key commercial workflows, such as art generation and image editing. Characterising the implicit social biases they exhibit, such as gender and racial stereotypes, is a necessary first…

Computers and Society · Computer Science 2023-12-19 Adhithya Prakash Saravanan , Rafal Kocielnik , Roy Jiang , Pengrui Han , Anima Anandkumar

Painting is one of the ways for people to express their ideas, but what if people with disabilities in hands want to paint? To tackle this challenge, we create an end-to-end solution that can generate artistic images from text descriptions.…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Qinghe Tian , Jean-Claude Franchitti

Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel diffusion approach for text generation via text-guided image…

Computation and Language · Computer Science 2023-05-09 Junyi Li , Wayne Xin Zhao , Jian-Yun Nie , Ji-Rong Wen

Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Doyeon Kim , Donggyu Joo , Junmo Kim

The generative modeling landscape has experienced tremendous growth in recent years, particularly in generating natural images and art. Recent techniques have shown impressive potential in creating complex visual compositions while…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Juan A Rodriguez , David Vazquez , Issam Laradji , Marco Pedersoli , Pau Rodriguez

Text-to-image diffusion models enable high-quality image generation but are computationally expensive. While prior work optimizes per-inference efficiency, we explore an orthogonal approach: reducing redundancy across correlated prompts.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Dale Decatur , Thibault Groueix , Wang Yifan , Rana Hanocka , Vladimir Kim , Matheus Gadelha

Diffusion models have demonstrated exceptional capabilities in generating a broad spectrum of visual content, yet their proficiency in rendering text is still limited: they often generate inaccurate characters or words that fail to blend…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jianyi Zhang , Yufan Zhou , Jiuxiang Gu , Curtis Wigington , Tong Yu , Yiran Chen , Tong Sun , Ruiyi Zhang

Text-to-image diffusion models have demonstrated tremendous success in synthesizing visually stunning images given textual instructions. Despite remarkable progress in creating high-fidelity visuals, text-to-image models can still struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Taewook Kim , Ze Wang , Zhengyuan Yang , Jiang Wang , Lijuan Wang , Zicheng Liu , Qiang Qiu

Community consultations are integral to urban planning processes intended to incorporate diverse stakeholder perspectives. However, limited resources, visual and spoken language barriers, and uneven power dynamics frequently constrain…

Human-Computer Interaction · Computer Science 2025-09-16 Rashid Mushkani , Hugo Berard , Shin Koseki

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee
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