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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.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Urban pattern: Layout design by hierarchical domain splitting
Yong-Liang Yang, Jun Wang, Etienne Vouga, and Peter Wonka · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Learning layouts for single-pagegraphic designs
Peter O’Donovan, Aseem Agarwala, and Aaron Hertzmann · 2014
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On the theory of stochastic processes, with particular reference to applications
William Feller · 2015
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Designscape: Design with interactive layout suggestions
Peter O’Donovan, Aseem Agarwala, and Aaron Hertzmann · 2015
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Directing user attention via visual flow on web designs
Xufang Pang, Ying Cao, Rynson WH Lau, and Antoni B Chan · 2016
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Rico: A mobile app dataset for building data-driven design applications
Biplab Deka, Zifeng Huang, Chad Franzen, Joshua Hibschman, Daniel Afergan, Yang Li, Jeffrey Nichols, and Ranjitha Kumar · 2017
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A learned representation for artistic style
Vincent Dumoulin, Jonathon Shlens, and Manjunath Kudlur · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Layoutvae: Stochastic scene layout generation from a label set
Akash Abdu Jyothi, Thibaut Durand, Jiawei He, Leonid Sigal, and Greg Mori · 2019
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Content-aware generative modeling of graphic design layouts
Xinru Zheng, Xiaotian Qiao, Ying Cao, and Rynson WH Lau · 2019
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Publaynet: largest dataset ever for document layout analysis
Xu Zhong, Jianbin Tang, and Antonio Jimeno Yepes · 2019
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Neural design network: Graphic layout generation with constraints
Hsin-Ying Lee, Lu Jiang, Irfan Essa, Phuong B Le, Haifeng Gong, Ming-Hsuan Yang, and Weilong Yang · 2020
Cited alongside, same era.
Attribute-conditioned layout gan for automatic graphic design
Jianan Li, Jimei Yang, Jianming Zhang, Chang Liu, Christina Wang, and Tingfa Xu · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Variational transformer networks for layout generation
Card: Classification and regression diffusion models
Xizewen Han, Huangjie Zheng, and Mingyuan Zhou · 2022
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Unilayout: Taming unified sequence-to-sequence transformers for graphic layout generation
Zhaoyun Jiang, Huayu Deng, Zhongkai Wu, Jiaqi Guo, Shizhao Sun, Vuksan Mijovic, Zijiang Yang, Jian-Guang Lou, and Dongmei Zhang · 2022
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Blt: bidirectional layout transformer for controllable layout generation
Xiang Kong, Lu Jiang, Huiwen Chang, Han Zhang, Yuan Hao, Haifeng Gong, and Irfan Essa · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
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Layoutdm: Transformer-based diffusion model for layout generation
Shang Chai, Liansheng Zhuang, and Fengying Yan · 2023
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Diego Martin Arroyo, Janis Postels, and Federico Tombari · 2021
Cited alongside, same era.
Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne Van Den Berg · 2021
Cited alongside, same era.
Layouttransformer: Layout generation and completion with self-attention
Kamal Gupta, Justin Lazarow, Alessandro Achille, Larry S Davis, Vijay Mahadevan, and Abhinav Shrivastava · 2021
Cited alongside, same era.
Constrained graphic layout generation via latent optimization
Kotaro Kikuchi, Edgar Simo-Serra, Mayu Otani, and Kota Yamaguchi · 2021
Cited alongside, same era.
Ruite: Refining ui layout aesthetics using transformer encoder
Soliha Rahman, Vinoth Pandian Sermuga Pandian, and Matthias Jarke · 2021
Cited alongside, same era.
Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T Freeman · 2022
Cited alongside, same era.
Vector quantized diffusion model for text-to-image synthesis
Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, and Baining Guo · 2022
Cited alongside, same era.
Chin-Yi Cheng, Forrest Huang, Gang Li, and Yang Li · 2023
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Diffusion-based document layout generation
Liu He, Yijuan Lu, John Corring, Dinei Florencio, and Cha Zhang · 2023
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Unifying layout generation with a decoupled diffusion model
Mude Hui, Zhizheng Zhang, Xiaoyi Zhang, Wenxuan Xie, Yuwang Wang, and Yan Lu · 2023
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Layoutdm: Discrete diffusion model for controllable layout generation
Naoto Inoue, Kotaro Kikuchi, Edgar Simo-Serra, Mayu Otani, and Kota Yamaguchi · 2023
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Layoutformer++: Conditional graphic layout generation via constraint serialization and decoding space restriction
Zhaoyun Jiang, Jiaqi Guo, Shizhao Sun, Huayu Deng, Zhongkai Wu, Vuksan Mijovic, Zijiang James Yang, Jian-Guang Lou, and Dongmei Zhang · 2023
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Diffusion models as masked autoencoders
Chen Wei, Karttikeya Mangalam, Po-Yao Huang, Yanghao Li, Haoqi Fan, Hu Xu, Huiyu Wang, Cihang Xie, Alan Yuille, and Christoph Feichtenhofer · 2023
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Layoutdiffusion: Improving graphic layout generation by discrete diffusion probabilistic models
Junyi Zhang, Jiaqi Guo, Shizhao Sun, Jian-Guang Lou, and Dongmei Zhang · 2023
Later among the works it cites.