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Indoor scene synthesis involves automatically picking and placing furniture appropriately on a floor plan, so that the scene looks realistic and is functionally plausible.
Object associations: a simple and practical approach to virtual 3d manipulation
Richard W. Bukowski and Carlo H. Séquin · 1995
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Constraint-based automatic placement for scene composition
Ken Xu, James Stewart, and Eugene Fiume · 2002
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Procedural modeling of buildings
Pascal Müller, Peter Wonka, Simon Haegler, Andreas Ulmer, and Luc Van Gool · 2006
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Procedural arrangement of furniture for real-time walkthroughs
Tobias Germer and Martin Schwarz · 2009
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Interactive furniture layout using interior design guidelines
Paul Merrell, Eric Schkufza, Zeyang Li, Maneesh Agrawala, and Vladlen Koltun · 2011
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Metropolis procedural modeling
Jerry O. Talton, Yu Lou, Steve Lesser, Jared Duke, Radomír Měch, and Vladlen Koltun · 2011
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Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Domain randomization for transferring deep neural networks from simulation to the real world, 2017
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
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Attention is all you need, 2017
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Pixelcnn++: Improving the pixelcnn with discretized logistic mixture likelihood and other modifications, 2017
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P. Kingma · 2017
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Structured domain randomization: Bridging the reality gap by context-aware synthetic data, 2018
Aayush Prakash, Shaad Boochoon, Mark Brophy, David Acuna, Eric Cameracci, Gavriel State, Omer Shapira, and Stan Birchfield · 2018
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Grains: Generative recursive autoencoders for indoor scenes, 2018
Manyi Li, Akshay Gadi Patil, Kai Xu, Siddhartha Chaudhuri, Owais Khan, Ariel Shamir, Changhe Tu, Baoquan Chen, Daniel Cohen-Or, and Hao Zhang · 2018
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Deep generative modeling for scene synthesis via hybrid representations, 2018
Zaiwei Zhang, Zhenpei Yang, Chongyang Ma, Linjie Luo, Alexander Huth, Etienne Vouga, and Qixing Huang · 2018
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Fast and flexible indoor scene synthesis via deep convolutional generative models, 2018
Daniel Ritchie, Kai Wang, and Yu-an Lin · 2018
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Deep convolutional priors for indoor scene synthesis
Kai Wang, Manolis Savva, Angel X. Chang, and Daniel Ritchie · 2018
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Human-centric indoor scene synthesis using stochastic grammar, 2018
Siyuan Qi, Yixin Zhu, Siyuan Huang, Chenfanfu Jiang, and Song-Chun Zhu · 2018
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Blender - a 3D modelling and rendering package
Blender Online Community · 2018
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A survey of 3d indoor scene synthesis
Song Hai Zhang, Shao Kui Zhang, Yuan Liang, and Peter Hall · 2019
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Meta-sim: Learning to generate synthetic datasets, 2019
Amlan Kar, Aayush Prakash, Ming-Yu Liu, Eric Cameracci, Justin Yuan, Matt Rusiniak, David Acuna, Antonio Torralba, and Sanja Fidler · 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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Scenegraphnet: Neural message passing for 3d indoor scene augmentation, 2019
Yang Zhou, Zachary While, and Evangelos Kalogerakis · 2019
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Sg-vae: Scene grammar variational autoencoder to generate new indoor scenes, 2019
Pulak Purkait, Christopher Zach, and Ian Reid · 2019
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Meta-sim2: Unsupervised learning of scene structure for synthetic data generation, 2020
Learning transferable visual models from natural language supervision, 2021
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Contextual scene augmentation and synthesis via gsacnet, 2021
Mohammad Keshavarzi, Flaviano Christian Reyes, Ritika Shrivastava, Oladapo Afolabi, Luisa Caldas, and Allen Y. Yang · 2021
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Neural fields in visual computing and beyond, 2021
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, and Srinath Sridhar · 2021
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Clip-forge: Towards zero-shot text-to-shape generation, 2021
Aditya Sanghi, Hang Chu, Joseph G. Lambourne, Ye Wang, Chin-Yi Cheng, Marco Fumero, and Kamal Rahimi Malekshan · 2021
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Procthor: Large-scale embodied ai using procedural generation, 2022
Matt Deitke, Eli VanderBilt, Alvaro Herrasti, Luca Weihs, Jordi Salvador, Kiana Ehsani, Winson Han, Eric Kolve, Ali Farhadi, Aniruddha Kembhavi, and Roozbeh Mottaghi · 2022
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Jeevan Devaranjan, Amlan Kar, and Sanja Fidler · 2020
Cited alongside, same era.
End-to-end optimization of scene layout, 2020
Andrew Luo, Zhoutong Zhang, Jiajun Wu, and Joshua B. Tenenbaum · 2020
Cited alongside, same era.
Fast 3d indoor scene synthesis with discrete and exact layout pattern extraction, 2020
Song-Hai Zhang, Shao-Kui Zhang, Wei-Yu Xie, Cheng-Yang Luo, and Hong-Bo Fu · 2020
Cited alongside, same era.
Sceneformer: Indoor scene generation with transformers, 2020
Xinpeng Wang, Chandan Yeshwanth, and Matthias Nießner · 2020
Cited alongside, same era.
3d-front: 3d furnished rooms with layouts and semantics, 2020
Huan Fu, Bowen Cai, Lin Gao, Lingxiao Zhang, Jiaming Wang Cao Li, Zengqi Xun, Chengyue Sun, Rongfei Jia, Binqiang Zhao, and Hao Zhang · 2020
Cited alongside, same era.
Scenegen: Generative contextual scene augmentation using scene graph priors, 2020
Mohammad Keshavarzi, Aakash Parikh, Xiyu Zhai, Melody Mao, Luisa Caldas, and Allen Y. Yang · 2020
Cited alongside, same era.
Transformers are rnns: Fast autoregressive transformers with linear attention
A. Katharopoulos, A. Vyas, N. Pappas, and F. Fleuret · 2020
Cited alongside, same era.
Gaudi: A neural architect for immersive 3d scene generation
Miguel Angel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, and Josh Susskind · 2022
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Mime: Human-aware 3d scene generation, 2022
Hongwei Yi, Chun-Hao P. Huang, Shashank Tripathi, Lea Hering, Justus Thies, and Michael J. Black · 2022
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Mutual scene synthesis for mixed reality telepresence, 2022
Mohammad Keshavarzi, Michael Zollhoefer, Allen Y. Yang, Patrick Peluse, and Luisa Caldas · 2022
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3dilg: Irregular latent grids for 3d generative modeling, 2022
Biao Zhang, Matthias Nießner, and Peter Wonka · 2022
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Get3d: A generative model of high quality 3d textured shapes learned from images, 2022
Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, and Sanja Fidler · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2022
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Lion: Latent point diffusion models for 3d shape generation, 2022
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis · 2022
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On aliased resizing and surprising subtleties in gan evaluation
Gaurav Parmar, Richard Zhang, and Jun-Yan Zhu · 2022
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Layoutenhancer: Generating good indoor layouts from imperfect data
Kurt Leimer, Paul Guerrero, Tomer Weiss, and Przemyslaw Musialski · 2022
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Scenedreamer: Unbounded 3d scene generation from 2d image collections, 2023
Zhaoxi Chen, Guangcong Wang, and Ziwei Liu · 2023
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Text2room: Extracting textured 3d meshes from 2d text-to-image models, 2023
Lukas Höllein, Ang Cao, Andrew Owens, Justin Johnson, and Matthias Nießner · 2023
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