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A critical obstacle preventing NeRF models from being deployed broadly in the wild is their reliance on accurate camera poses.
Shape ambiguities in structure from motion
Rick Szeliski and Sing Bing Kang · 1997
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Multiple view geometry in computer vision
Richard Hartley and Andrew Zisserman · 2003
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Distinctive image features from scale-invariant keypoints
David G. Lowe · 2004
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Two-view geometry estimation unaffected by a dominant plane
Ondrej Chum, Tomás Werner, and Jiri Matas · 2005
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Multibody structure-from-motion in practice
Kemal Egemen Ozden, Konrad Schindler, and Luc Van Gool · 2010
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Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
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Sensor network localization by eigenvector synchronization over the euclidean group
Mihai Cucuringu, Yaron Lipman, and Amit Singer · 2012
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Rotation Averaging
Richard Hartley, Jochen Trumpf, Yuchao Dai, and Hongdong Li · 2013
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Divide and conquer: Efficient large-scale structure from motion using graph partitioning
Brojeshwar Bhowmick, Suvam Patra, Avishek Chatterjee, Venu Madhav Govindu, and Subhashis Banerjee · 2015
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ORB-SLAM: a versatile and accurate monocular SLAM system
Raúl Mur-Artal, J. M. M. Montiel, and Juan D. Tardós · 2015
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Spectral synchronization of multiple views in se(3)
Federica Arrigoni, Beatrice Rossi, and Andrea Fusiello · 2016
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Structure-from-Motion Revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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A survey of structure from motion
Onur Özyeşil, Vladislav Voroninski, Ronen Basri, and Amit Singer · 2017
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Visual slam algorithms: A survey from 2010 to 2016
Takafumi Taketomi, Hideaki Uchiyama, and Sei Ikeda · 2017
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Superpoint: Self-supervised interest point detection and description, 2018
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2018
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Unsupervised learning of shape and pose with differentiable point clouds
Eldar Insafutdinov and Alexey Dosovitskiy · 2018
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Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida · 2018
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Multi-view consistency as supervisory signal for learning shape and pose prediction
Shubham Tulsiani, Alexei A. Efros, and Jitendra Malik · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
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Very large-scale global sfm by distributed motion averaging
Siyu Zhu, Runze Zhang, Lei Zhou, Tianwei Shen, Tian Fang, Ping Tan, and Long Quan · 2018
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Merge-sfm: Merging partial reconstructions
Meiling Fang, Thomas Pollok, and Chengchao Qu · 2019
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SE-Sync: A certifiably correct algorithm for synchronization over the special euclidean group
David M Rosen, Luca Carlone, Afonso S Bandeira, and John J Leonard · 2019
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From coarse to fine: Robust hierarchical localization at large scale
Paul-Edouard Sarlin, Cesar Cadena, Roland Siegwart, and Marcin Dymczyk · 2019
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Graph-based parallel large scale structure from motion
Yu Chen, Shuhan Shen, Yisong Chen, and Guoping Wang · 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
Cited alongside, same era.
Superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
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Nope-nerf: Optimising neural radiance field with no pose prior
Wenjing Bian, Zirui Wang, Kejie Li, Jia-Wang Bian, and Victor Adrian Prisacariu · 2022
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SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Mark Boss, Andreas Engelhardt, Abhishek Kar, Yuanzhen Li, Deqing Sun, Jonathan T. Barron, Hendrik P.A. Lensch, and Varun Jampani · 2022
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GeoAug: Data augmentation for few-shot nerf with geometry constraints
Di Chen, Yu Liu, Lianghua Huang, Bin Wang, and Pan Pan · 2022
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Structure-aware nerf without posed camera via epipolar constraint
Shu Chen, Yang Zhang, Yaxin Xu, and Beiji Zou · 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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Shangzhe Wu, Christian Rupprecht, and Andrea Vedaldi · 2020
Cited alongside, same era.
Stochastic bundle adjustment for efficient and scalable 3d reconstruction
Lei Zhou, Zixin Luo, Mingmin Zhen, Tianwei Shen, Shiwei Li, Zhuofei Huang, Tian Fang, and Long Quan · 2020
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Objectron: A large scale dataset of object-centric videos in the wild with pose annotations
Adel Ahmadyan, Liangkai Zhang, Artsiom Ablavatski, Jianing Wei, and Matthias Grundmann · 2021
Cited alongside, same era.
Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 2021
Cited alongside, same era.
Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
Cited alongside, same era.
Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Cited alongside, same era.
Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
Anpei Chen, Zexiang Xu, Fuqiang Zhao, Xiaoshuai Zhang, Fanbo Xiang, Jingyi Yu, and Hao Su · 2021
Cited alongside, same era.
ViewFormer: NeRF-free neural rendering from few images using transformers
Jonáš Kulhánek, Erik Derner, Torsten Sattler, and Robert Babuška · 2022
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BARF: Bundle-adjusting neural radiance fields
Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey · 2022
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Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency
Tom Monnier, Matthew Fisher, Alexei A. Efros, and Mathieu Aubry · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 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
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Cross-spectral neural radiance fields
Matteo Poggi, Pierluigi Zama Ramirez, Fabio Tosi, Samuele Salti, Stefano Mattoccia, and Luigi Di Stefano · 2022
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Nerf-slam: Real-time dense monocular slam with neural radiance fields
Antoni Rosinol, John J Leonard, and Luca Carlone · 2022
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Advances in neural rendering
A. Tewari, J. Thies, B. Mildenhall, P. Srinivasan, E. Tretschk, W. Yifan, C. Lassner, V. Sitzmann, R. Martin-Brualla, S. Lombardi, T. Simon, C. Theobalt, M. Nießner, J. T. Barron, G. Wetzstein, M. Zollhöfer, and V. Golyanik · 2022
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Sinerf: Sinusoidal neural radiance fields for joint pose estimation and scene reconstruction
Yitong Xia, Hao Tang, Radu Timofte, and Luc Van Gool · 2022
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Neural fields in visual computing and beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, and Srinath Sridhar · 2022
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Vmrf: View matching neural radiance fields
Jiahui Zhang, Fangneng Zhan, Rongliang Wu, Yingchen Yu, Wenqing Zhang, Bai Song, Xiaoqin Zhang, and Shijian Lu · 2022
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Nice-slam: Neural implicit scalable encoding for slam
Zihan Zhu, Songyou Peng, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R Oswald, and Marc Pollefeys · 2022
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MELON: Nerf with unposed images using equivalence class estimation
Axel Levy, Mark Matthews, Matan Sela, Gordon Wetzstein, and Dmitry Lagun · 2023
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Progressively optimized local radiance fields for robust view synthesis
Andreas Meuleman, Yu-Lun Liu, Chen Gao, Jia-Bin Huang, Changil Kim, Min H Kim, and Johannes Kopf · 2023
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RUST: Latent Neural Scene Representations from Unposed Imagery
Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lučić, and Klaus Greff · 2023
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Flowcam:training generalizable 3d radiance fields without camera poses via pixel-aligned scene flow
Cameron Smith, Yilun Du, Ayush Tewari, and Vincent Sitzmann · 2023
Closest in time.