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We consider the task of generating designs directly from natural language descriptions, and consider floor plan generation as the initial research area. Language conditional generative models have recently been very successful in generating…

Computation and Language · Computer Science 2023-11-28 Sicong Leng , Yang Zhou , Mohammed Haroon Dupty , Wee Sun Lee , Sam Conrad Joyce , Wei Lu

Text-to-image diffusion models exhibit remarkable generative capabilities, but lack precise control over object counts and spatial arrangements. This work introduces a two-stage system to address these compositional limitations. The first…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Jan-Hendrik Koch , Jonas Krumme , Konrad Gadzicki

Conditional graphic layout generation, which automatically maps user constraints to high-quality layouts, has attracted widespread attention today. Although recent works have achieved promising performance, the lack of versatility and data…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Jiawei Lin , Jiaqi Guo , Shizhao Sun , Zijiang James Yang , Jian-Guang Lou , Dongmei Zhang

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

Graph diffusion models achieve state-of-the-art performance in graph generation but suffer from quadratic complexity in the number of nodes -- and much of their capacity is wasted modeling the absence of edges in sparse graphs. Inspired by…

Machine Learning · Computer Science 2026-05-13 Antoine Siraudin , Christopher Morris

The generation and editing of floor plans are critical in architectural planning, requiring a high degree of flexibility and efficiency. Existing methods demand extensive input information and lack the capability for interactive adaptation…

Human-Computer Interaction · Computer Science 2024-10-17 Sizhong Qin , Chengyu He , Qiaoyun Chen , Sen Yang , Wenjie Liao , Yi Gu , Xinzheng Lu

Text conditioned generative models for images have yielded impressive results. Text conditioned floorplan generation as a special type of raster image generation task also received particular attention. However there are many use cases in…

Computation and Language · Computer Science 2024-07-23 Zhi Hao Luo , Luis Lara , Ge Ya Luo , Florian Golemo , Christopher Beckham , Christopher Pal

GUI (graphical user interface) prototyping is a widely-used technique in requirements engineering for gathering and refining requirements, reducing development risks and increasing stakeholder engagement. However, GUI prototyping can be a…

Software Engineering · Computer Science 2023-10-05 Jialiang Wei , Anne-Lise Courbis , Thomas Lambolais , Binbin Xu , Pierre Louis Bernard , Gérard Dray

Recent progress in image generation has sparked research into controlling these models through condition signals, with various methods addressing specific challenges in conditional generation. Instead of proposing another specialized…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xirui Li , Charles Herrmann , Kelvin C. K. Chan , Yinxiao Li , Deqing Sun , Chao Ma , Ming-Hsuan Yang

We present SemLayoutDiff, a unified model for synthesizing diverse 3D indoor scenes across multiple room types. The model introduces a scene layout representation combining a top-down semantic map and attributes for each object. Unlike…

Graphics · Computer Science 2025-09-09 Xiaohao Sun , Divyam Goel , Angel X. Chang

Recent diffusion-based generative models show promise in their ability to generate text images, but limitations in specifying the styles of the generated texts render them insufficient in the realm of typographic design. This paper proposes…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 KhayTze Peong , Seiichi Uchida , Daichi Haraguchi

Conditioning image generation on specific features of the desired output is a key ingredient of modern generative models. However, existing approaches lack a general and unified way of representing structural and semantic conditioning at…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Luca Butera , Andrea Cini , Alberto Ferrante , Cesare Alippi

Diffusion-based text-to-image personalization have achieved great success in generating subjects specified by users among various contexts. Even though, existing finetuning-based methods still suffer from model overfitting, which greatly…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Henglei Lv , Jiayu Xiao , Liang Li , Qingming Huang

Recent advances in denoising diffusion models have enabled rapid generation of optimized structures for topology optimization. However, these models often rely on surrogate predictors to enforce physical constraints, which may fail to…

Machine Learning · Computer Science 2025-08-05 Euihyun Kim , Keun Park , Yeoneung Kim

In the field of graphic design, automating the integration of design elements into a cohesive multi-layered artwork not only boosts productivity but also paves the way for the democratization of graphic design. One existing practice is…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Yutao Cheng , Zhao Zhang , Maoke Yang , Hui Nie , Chunyuan Li , Xinglong Wu , Jie Shao

The rapid evolution of the fashion industry increasingly intersects with technological advancements, particularly through the integration of generative AI. This study introduces a novel generative pipeline designed to transform the fashion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Abhishek Kumar Singh , Ioannis Patras

Diffusion models have made significant contributions to computer vision, sparking a growing interest in the community recently regarding the application of them to graph generation. Existing discrete graph diffusion models exhibit…

Machine Learning · Computer Science 2024-05-07 Xingcheng Fu , Yisen Gao , Yuecen Wei , Qingyun Sun , Hao Peng , Jianxin Li , Xianxian Li

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

The Latent Diffusion Model (LDM) has demonstrated strong capabilities in high-resolution image generation and has been widely employed for Pose-Guided Person Image Synthesis (PGPIS), yielding promising results. However, the compression…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Jiaqi Liu , Jichao Zhang , Paolo Rota , Nicu Sebe

In this paper we describe a learned method of traffic scene generation designed to simulate the output of the perception system of a self-driving car. In our "Scene Diffusion" system, inspired by latent diffusion, we use a novel combination…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Ethan Pronovost , Kai Wang , Nick Roy