LayoutDM: Transformer-based Diffusion Model for Layout Generation-Reference-Cited by-同舟云学术

LayoutDM: Transformer-based Diffusion Model for Layout Generation

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
Short-container-title:

Author:

Chai Shang¹,Zhuang Liansheng¹,Yan Fengying²

Affiliation:

1. University of Science and Technology of China

2. Tianjin University

Funder

NSFC

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10204668.pdf?arnumber=10204668

Reference47 articles.

1. Classifier-free diffusion guidance;ho;ArXiv,2022

2. Gans trained by a two time-scale update rule converge to a local nash equilibrium;heusel;Proceedings of the 31st International Conference on Neural Information Processing Systems NIPS'17,2017

3. Generating diverse high-fidelity images with vq-vae-2;razavi;Advances in neural information processing systems,2019

4. Coarse-to-Fine Generative Modeling for Graphic Layouts

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. House Layout Generation via Diffusion Model with Relative Room Area Ranking;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. From Algorithms to Architecture: Computational Methods for House Floorplan Generation;SN Computer Science;2024-05-27

3. On Improving the Qualitative Features of the User Interface of Mobile Applications Using Machine Learning Methods;2024 47th MIPRO ICT and Electronics Convention (MIPRO);2024-05-20

4. Latent diffusion transformer for point cloud generation;The Visual Computer;2024-04-22

5. A Comprehensive Survey of Recent Transformers in Image, Video and Diffusion Models;Computers, Materials & Continua;2024