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What constitutes the "vibe" of a particular scene? What should one find in "a busy, dirty city street", "an idyllic countryside", or "a crime scene in an abandoned living room"? The translation from abstract scene descriptions to stylized scene elements cannot be done with any generality by extant systems trained on rigid and limited indoor datasets.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901
Earlier work this paper cites.
Text to 3d scene generation with rich lexical grounding
Angel Chang, Will Monroe, Manolis Savva, Christopher Potts, and Christopher D Manning. 2015b · 2015
Earlier work this paper cites.
Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
Earlier work this paper cites.
Sun rgb-d: A rgb-d scene understanding benchmark suite. In Proceedings of the IEEE conference on computer vision and pattern recognition . 567–576
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao. 2015 · 2015
Earlier work this paper cites.
Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang. 2017 · 2017
Earlier work this paper cites.
Semantic scene completion from a single depth image. In Proceedings of the IEEE conference on computer vision and pattern recognition . 1746–1754
Shuran Song, Fisher Yu, Andy Zeng, Angel X Chang, Manolis Savva, and Thomas Funkhouser. 2017 · 2017
Earlier work this paper cites.
Blender - a 3D modelling and rendering package
Blender Online Community. 2018 · 2018
Earlier work this paper cites.
Language-driven synthesis of 3D scenes from scene databases
Rui Ma, Akshay Gadi Patil, Matthew Fisher, Manyi Li, Sören Pirk, Binh-Son Hua, Sai-Kit Yeung, Xin Tong, Leonidas Guibas, and Hao Zhang. 2018 · 2018
Earlier work this paper cites.
Tell me more: A dataset of visual scene description sequences. In Proceedings of the 12th international conference on natural language generation . 152–157
Nikolai Ilinykh, Sina Zarrieß, and David Schlangen. 2019 · 2019
Earlier work this paper cites.
Fast and flexible indoor scene synthesis via deep convolutional generative models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 6182–6190
Daniel Ritchie, Kai Wang, and Yu-an Lin. 2019 · 2019
Earlier work this paper cites.
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 · 2019
Earlier work this paper cites.
Referit3d: Neural listeners for fine-grained 3d object identification in real-world scenes. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I 16 . Springer, 422–440
Panos Achlioptas, Ahmed Abdelreheem, Fei Xia, Mohamed Elhoseiny, and Leonidas Guibas. 2020 · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
Earlier work this paper cites.
3d-future: 3d furniture shape with texture
Huan Fu, Rongfei Jia, Lin Gao, Mingming Gong, Binqiang Zhao, Steve Maybank, and Dacheng Tao. 2021b · 2021
Earlier work this paper cites.
Metaicl: Learning to learn in context
Sewon Min, Mike Lewis, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2021 · 2021
Earlier work this paper cites.
Atiss: Autoregressive transformers for indoor scene synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, and Sanja Fidler. 2021 · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding. In International Conference on Computer Vision (ICCV) 2021
Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Angel Bautista, Nathan Paczan, Russ Webb, and Joshua M. Susskind. 2021 · 2021
Earlier work this paper cites.
Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant. 2021 · 2021
Cited alongside, same era.
BuildingNet: Learning to label 3D buildings. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 10397–10407
Pratheba Selvaraju, Mohamed Nabail, Marios Loizou, Maria Maslioukova, Melinos Averkiou, Andreas Andreou, Siddhartha Chaudhuri, and Evangelos Kalogerakis. 2021 · 2021
Cited alongside, same era.
Sceneformer: Indoor scene generation with transformers. In 2021 International Conference on 3D Vision (3DV) . IEEE, 106–115
Xinpeng Wang, Chandan Yeshwanth, and Matthias Nießner. 2021 · 2021
Cited alongside, same era.
Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2021 · 2021
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall. 2022 · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
Later among the works it cites.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Later among the works it cites.
Clip-forge: Towards zero-shot text-to-shape generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 18603–18613
Aditya Sanghi, Hang Chu, Joseph G Lambourne, Ye Wang, Chin-Yi Cheng, Marco Fumero, and Kamal Rahimi Malekshan. 2022 · 2022
Later among the works it cites.
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Calibrate before use: Improving few-shot performance of language models. In International Conference on Machine Learning . PMLR, 12697–12706
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
Cited alongside, same era.
ChangeIt3D: Language-Assisted 3D Shape Edits and Deformations
Panos Achlioptas, Ian Huang, Minhyuk Sung, Sergey Tulyakov, and Leonidas Guibas. 2022 · 2022
Cited alongside, same era.
Improving In-Context Few-Shot Learning via Self-Supervised Training
Mingda Chen, Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov, Srini Iyer, Veselin Stoyanov, and Zornitsa Kozareva. 2022 · 2022
Cited alongside, same era.
Objaverse: A Universe of Annotated 3D Objects
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi. 2022 · 2022
Cited alongside, same era.
A Survey for In-context Learning
Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, and Zhifang Sui. 2022 · 2022
Cited alongside, same era.
Shapecrafter: A recursive text-conditioned 3d shape generation model
Rao Fu, Xiao Zhan, Yiwen Chen, Daniel Ritchie, and Srinath Sridhar. 2022 · 2022
Cited alongside, same era.
Get3d: A generative model of high quality 3d textured shapes learned from images
Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, and Sanja Fidler. 2022 · 2022
Cited alongside, same era.
LADIS: Language disentanglement for 3D shape editing
Ian Huang, Panos Achlioptas, Tianyi Zhang, Sergey Tulyakov, Minhyuk Sung, and Leonidas Guibas. 2022 · 2022
Cited alongside, same era.
Seongjin Shin, Sang-Woo Lee, Hwijeen Ahn, Sungdong Kim, HyoungSeok Kim, Boseop Kim, Kyunghyun Cho, Gichang Lee, Woomyoung Park, Jung-Woo Ha, et al · 2022
Later among the works it cites.
Iteratively prompt pre-trained language models for chain of thought. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing . 2714–2730
Boshi Wang, Xiang Deng, and Huan Sun. 2022 · 2022
Later among the works it cites.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.
Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models
Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao, Ying Shan, Xiaohu Qie, and Shenghua Gao. 2022 · 2022
Later among the works it cites.
When and why vision-language models behave like bags-of-words, and what to do about it?
Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, and James Zou. 2022 · 2022
Later among the works it cites.
Automatic chain of thought prompting in large language models
Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola. 2022 · 2022
Later among the works it cites.
Least-to-most prompting enables complex reasoning in large language models
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, and Ed Chi. 2022 · 2022
Later among the works it cites.
Scenescape: Text-driven consistent scene generation
Rafail Fridman, Amit Abecasis, Yoni Kasten, and Tali Dekel. 2023 · 2023
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Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models
Lukas Höllein, Ang Cao, Andrew Owens, Justin Johnson, and Matthias Nießner. 2023 · 2023
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Shap-E: Generating Conditional 3D Implicit Functions
Heewoo Jun and Alex Nichol. 2023 · 2023
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Compositional 3D Scene Generation using Locally Conditioned Diffusion
Ryan Po and Gordon Wetzstein. 2023 · 2023
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TEXTure: Text-Guided Texturing of 3D Shapes
Elad Richardson, Gal Metzer, Yuval Alaluf, Raja Giryes, and Daniel Cohen-Or. 2023 · 2023
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Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields
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