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We address the problem of scene layout generation for diverse domains such as images, mobile applications, documents, and 3D objects.
On the semantics of a glance at a scene
Irving Biederman · 1981
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Improvements in beam search
Volker Steinbiss, Bach-Hiep Tran, and Hermann Ney · 1994
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Statistical context priming for object detection
Antonio Torralba and Pawan Sinha · 2001
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Auto-encoding variational bayes, 2013
Diederik P Kingma and Max Welling · 2013
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 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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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Text to 3d scene generation with rich lexical grounding
Angel X. Chang, Will Monroe, Manolis Savva, Christopher Potts, and Christopher D. Manning · 2015
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Draw: A recurrent neural network for image generation
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, and Daan Wierstra · 2015
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Order matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, and Manjunath Kudlur · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2016
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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Contextual priming and feedback for faster r-cnn
Abhinav Shrivastava and Abhinav Gupta · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Generating videos with scene dynamics
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
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Docemul: a toolkit to generate structured historical documents
Samuele Capobianco and Simone Marinai · 2017
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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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Semantic image synthesis via adversarial learning
Hao Dong, Simiao Yu, Chao Wu, and Yike Guo · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
Cited alongside, same era.
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P Kingma · 2017
Cited alongside, same era.
Complementme: weakly-supervised component suggestions for 3d modeling
Minhyuk Sung, Hao Su, Vladimir G Kim, Siddhartha Chaudhuri, and Leonidas Guibas · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Learning to see physics via visual de-animation
Jiajun Wu, Erika Lu, Pushmeet Kohli, William T Freeman, and Joshua B Tenenbaum · 2017
Cited alongside, same era.
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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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Seq-sg2sl: Inferring semantic layout from scene graph through sequence to sequence learning
Boren Li, Boyu Zhuang, Mingyang Li, and Jian Gu · 2019
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Layoutgan: Generating graphic layouts with wireframe discriminators
Jianan Li, Jimei Yang, Aaron Hertzmann, Jianming Zhang, and Tingfa Xu · 2019
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Grains: Generative recursive autoencoders for indoor scenes
Manyi Li, Akshay Gadi Patil, Kai Xu, Siddhartha Chaudhuri, Owais Khan, Ariel Shamir, Changhe Tu, Baoquan Chen, Daniel Cohen-Or, and Hao Zhang · 2019
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Neural scene de-rendering
Jiajun Wu, Joshua B Tenenbaum, and Pushmeet Kohli · 2017
Cited alongside, same era.
Xiao Yang, Mehmet Ersin Yümer, Paul Asente, Mike Kraley, Daniel Kifer, and C. Lee Giles · 2017
Cited alongside, same era.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas · 2017
Cited alongside, same era.
3d-prnn: Generating shape primitives with recurrent neural networks
Chuhang Zou, Ersin Yumer, Jimei Yang, Duygu Ceylan, and Derek Hoiem · 2017
Cited alongside, same era.
Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
Cited alongside, same era.
Inferring semantic layout for hierarchical text-to-image synthesis
Seunghoon Hong, Dingdong Yang, Jongwook Choi, and Honglak Lee · 2018
Cited alongside, same era.
Image generation from scene graphs
Justin Johnson, Agrim Gupta, and Li Fei-Fei · 2018
Cited alongside, same era.
Later among the works it cites.
Object-driven text-to-image synthesis via adversarial training
Wenbo Li, Pengchuan Zhang, Lei Zhang, Qiuyuan Huang, Xiaodong He, Siwei Lyu, and Jianfeng Gao · 2019
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Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas J Guibas · 2019
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When does label smoothing help?
Rafael Müller, Simon Kornblith, and Geoffrey E. Hinton · 2019
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DeepSDF: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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Read: Recursive autoencoders for document layout generation
Akshay Gadi Patil, Omri Ben-Eliezer, Or Perel, Hadar Averbuch-Elor, and Cornell Tech · 2019
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Fast and flexible indoor scene synthesis via deep convolutional generative models
Daniel Ritchie, Kai Wang, and Yu-an Lin · 2019
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Planit: Planning and instantiating indoor scenes with relation graph and spatial prior networks
Kai Wang, Yu-An Lin, Ben Weissmann, Manolis Savva, Angel X Chang, and Daniel Ritchie · 2019
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PointFlow: 3D point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
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Partnet: A recursive part decomposition network for fine-grained and hierarchical shape segmentation
Fenggen Yu, Kun Liu, Yan Zhang, Chenyang Zhu, and Kai Xu · 2019
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Image generation from layout
Bo Zhao, Lili Meng, Weidong Yin, and Leonid Sigal · 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
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Generative pretraining from pixels
Mark Chen, Alec Radford, Rewon Child, Jeff Wu, Heewoo Jun, Prafulla Dhariwal, David Luan, and Ilya Sutskever · 2020
Closest in time.
Improved modeling of 3d shapes with multi-view depth maps
Kamal Gupta, Susmija Jabbireddy, Ketul Shah, Abhinav Shrivastava, and Matthias Zwicker · 2020
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PatchVAE: Learning Local Latent Codes for Recognition
Kamal Gupta, Saurabh Singh, and Abhinav Shrivastava · 2020
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Learning structural similarity of user interface layouts using graph networks
Dipu Manandhar, Dan Ruta, and John Collomosse · 2020
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Pq-net: A generative part seq2seq network for 3d shapes
Rundi Wu, Yixin Zhuang, Kai Xu, Hao Zhang, and Baoquan Chen · 2020
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