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High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications.
The rendering equation
James T. Kajiya · 1986
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Marching cubes: A high resolution 3d surface construction algorithm
William E. Lorensen and Harvey E. Cline · 1987
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Poisson Surface Reconstruction
Michael Kazhdan, Matthew Bolitho, and Hugues Hoppe · 2006
Earlier work this paper cites.
Photo tourism: exploring photo collections in 3d
Noah Snavely, Steven M Seitz, and Richard Szeliski · 2006
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Multi-view stereo for community photo collections
Michael Goesele, Noah Snavely, Brian Curless, Hugues Hoppe, and Steven M. Seitz · 2007
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Efficient deep learning for stereo matching
Wenjie Luo, Alexander G. Schwing, and Raquel Urtasun · 2016
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Image patch matching using convolutional descriptors with euclidean distance
I. Melekhov, J. Kannala, and E. Rahtu · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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Learned multi-patch similarity
Wilfried Hartmann, Silvano Galliani, Michal Havlena, Luc Van Gool, and Konrad Schindler · 2017
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Working hard to know your neighbor’s margins: local descriptor learning loss
Anastasiya Mishchuk, Dmytro Mishkin, Filip Radenović, and Jiři Matas · 2017
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Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
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Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries
Junjie Hu, Mete Ozay, Yan Zhang, and Takayuki Okatani · 2018
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Deepv2d: Video to depth with differentiable structure from motion
Zachary Teed and Jia Deng · 2018
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Open3D: A modern library for 3D data processing
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2018
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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The Replica dataset: A digital replica of indoor spaces
Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J. Engel, Raul Mur-Artal, Carl Ren, Shobhit Verma, Anton Clarkson, Mingfei Yan, Brian Budge, Yajie Yan, Xiaqing Pan, June Yon, Yuyang Zou, Kimberly Leon, Nigel Carter, Jesus Briales, Tyler Gillingham, Elias Mueggler, Luis Pesqueira, Manolis Savva, Dhruv Batra, Hauke M. Strasdat, Renzo De Nardi, Michael Goesele, Steven Lovegrove, and Richard Newcombe · 2019
Earlier work this paper cites.
Normal assisted stereo depth estimation
Uday Kusupati, Shuo Cheng, Rui Chen, and Hao Su · 2020
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Consistent video depth estimation
Xuan Luo, Jia-Bin Huang, Richard Szeliski, Kevin Matzen, and Johannes Kopf · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Atlas: End-to-end 3d scene reconstruction from posed images
Zak Murez, Tarrence Van As, James Bartolozzi, Ayan Sinha, Vijay Badrinarayanan, and Andrew Rabinovich · 2020
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Deltas: Depth estimation by learning triangulation and densification of sparse points
Ayan Sinha, Zak Murez, James Bartolozzi, Vijay Badrinarayanan, and Andrew Rabinovich · 2020
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Visibility-aware multi-view stereo network
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, and Tian Fang · 2020
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Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans
Ainaz Eftekhar, Alexander Sax, Jitendra Malik, and Amir Zamir · 2021
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Point-based neural rendering with per-view optimization
Georgios Kopanas, Julien Philip, Thomas Leimkühler, and George Drettakis · 2021
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Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
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Depth-regularized optimization for 3d gaussian splatting in few-shot images
Jaeyoung Chung, Jeongtaek Oh, and Kyoung Mu Lee · 2023
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Relightable 3d gaussian: Real-time point cloud relighting with brdf decomposition and ray tracing
Jian Gao, Chun Gu, Youtian Lin, Hao Zhu, Xun Cao, Li Zhang, and Yao Yao · 2023
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Sparsenerf: Distilling depth ranking for few-shot novel view synthesis
Guangcong, Zhaoxi Chen, Chen Change Loy, and Ziwei Liu · 2023
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3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
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Flexible techniques for differentiable rendering with 3d gaussians
Leonid Keselman and Martial Hebert · 2023
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Nerfingmvs: Guided optimization of neural radiance fields for indoor multi-view stereo
Yi Wei, Shaohui Liu, Yongming Rao, Wang Zhao, Jiwen Lu, and Jie Zhou · 2021
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Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman · 2022
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Depth-supervised NeRF: Fewer views and faster training for free
Kangle Deng, Andrew Liu, Jun-Yan Zhu, and Deva Ramanan · 2022
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Neural 3d scene reconstruction with the manhattan-world assumption
Haoyu Guo, Sida Peng, Haotong Lin, Qianqian Wang, Guofeng Zhang, Hujun Bao, and Xiaowei Zhou · 2022
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Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
Michael Niemeyer, Jonathan T. Barron, Ben Mildenhall, Mehdi S. M. Sajjadi, Andreas Geiger, and Noha Radwan · 2022
Cited alongside, same era.
Dense depth priors for neural radiance fields from sparse input views
Barbara Roessle, Jonathan T. Barron, Ben Mildenhall, Pratul P. Srinivasan, and Matthias Nießner · 2022
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Edge-aware consistent stereo video depth estimation
Elena Kosheleva, Sunil Jaiswal, Faranak Shamsafar, Noshaba Cheema, Klaus Illgner-Fehns, and Philipp Slusallek · 2023
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CorresNeRF: Image correspondence priors for neural radiance fields
Yixing Lao, Xiaogang Xu, Zhipeng Cai, Xihui Liu, and Hengshuang Zhao · 2023
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Neuralangelo: High-fidelity neural surface reconstruction
Zhaoshuo Li, Thomas Müller, Alex Evans, Russell H Taylor, Mathias Unberath, Ming-Yu Liu, and Chen-Hsuan Lin · 2023
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Nerfstudio: A modular framework for neural radiance field development
Matthew Tancik, Ethan Weber, Evonne Ng, Ruilong Li, Brent Yi, Justin Kerr, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, David McAllister, and Angjoo Kanazawa · 2023
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Sparsegs: Real-time 360° sparse view synthesis using gaussian splatting
Haolin Xiong, Sairisheek Muttukuru, Rishi Upadhyay, Pradyumna Chari, and Achuta Kadambi · 2023
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Scannet++: A high-fidelity dataset of 3d indoor scenes
Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, and Angela Dai · 2023
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Rethinking inductive biases for surface normal estimation
Gwangbin Bae and Andrew J. Davison · 2024
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Sugar: Surface-aligned gaussian splatting for efficient 3d mesh reconstruction and high-quality mesh rendering
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2d gaussian splatting for geometrically accurate radiance fields
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StopThePop: Sorted Gaussian Splatting for View-Consistent Real-time Rendering
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Nerfmeshing: Distilling neural radiance fields into geometrically-accurate 3d meshes
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Depth anything: Unleashing the power of large-scale unlabeled data
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gsplat: An open-source library for gaussian splatting
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