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Neural implicit representations have recently become popular in simultaneous localization and mapping (SLAM), especially in dense visual SLAM.
Marching cubes: A high resolution 3d surface construction algorithm
William E Lorensen and Harvey E Cline · 1987
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Parallel tracking and mapping for small ar workspaces
Georg Klein and David Murray · 2007
Earlier work this paper cites.
Kinectfusion: Real-time dense surface mapping and tracking
R. A. Newcombe, S. Izadi, O. Hilliges, D. Molyneaux, D. Kim, A. J. Davison, P. Kohi, J. Shotton, S. Hodges, and A. Fitzgibbon · 2011
Earlier work this paper cites.
Dtam: Dense tracking and mapping in real-time
Richard A Newcombe, Steven J Lovegrove, and Andrew J Davison · 2011
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A benchmark for the evaluation of rgb-d slam systems
Jürgen Sturm, Nikolas Engelhard, Felix Endres, Wolfram Burgard, and Daniel Cremers · 2012
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Kintinuous: Spatially extended kinectfusion
Thomas Whelan, Michael Kaess, Maurice Fallon, Hordur Johannsson, John Leonard, and John McDonald · 2012
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Real-time camera tracking and 3d reconstruction using signed distance functions
Erik Bylow, Jürgen Sturm, Christian Kerl, Fredrik Kahl, and Daniel Cremers · 2013
Earlier work this paper cites.
Real-time 3d reconstruction at scale using voxel hashing
Matthias Nießner, Michael Zollhöfer, Shahram Izadi, and Marc Stamminger · 2013
Earlier work this paper cites.
Scene coordinate regression forests for camera relocalization in rgb-d images
Jamie Shotton, Ben Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, and Andrew Fitzgibbon · 2013
Earlier work this paper cites.
Orb-slam: a versatile and accurate monocular slam system
Raul Mur-Artal, Jose Maria Martinez Montiel, and Juan D Tardos · 2015
Earlier work this paper cites.
Elasticfusion: Dense slam without a pose graph
Thomas Whelan, Stefan Leutenegger, Renato Salas-Moreno, Ben Glocker, and Andrew Davison · 2015
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Cloudcompare
Daniel Girardeau-Montaut · 2016
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Structure-from-motion revisited
J. L. Schonberger and J. M. Frahm · 2016
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Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface reintegration
Angela Dai, Matthias Nießner, Michael Zollhöfer, Shahram Izadi, and Christian Theobalt · 2017
Earlier work this paper cites.
Direct sparse odometry
Jakob Engel, Vladlen Koltun, and Daniel Cremers · 2017
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evo: Python package for the evaluation of odometry and slam
Michael Grupp · 2017
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Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras
Raul Mur-Artal and Juan D Tardós · 2017
Earlier work this paper cites.
Demon: Depth and motion network for learning monocular stereo
Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, and Thomas Brox · 2017
Earlier work this paper cites.
Codeslam - learning a compact, optimisable representation for dense visual SLAM
Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, and Andrew J. Davison · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Deeptam: Deep tracking and mapping
Huizhong Zhou, Benjamin Ummenhofer, and Thomas Brox · 2018
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Earlier work this paper cites.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Earlier work this paper cites.
Differentiable volumetric rendering: Learning implicit 3D representations without 3D supervision
M. Niemeyer, L. Mescheder, M. Oechsle, and A. Geiger · 2019
Earlier work this paper cites.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Earlier work this paper cites.
BAD SLAM: bundle adjusted direct RGB-D SLAM
Thomas Schöps, Torsten Sattler, and Marc Pollefeys · 2019
Cited alongside, same era.
The Replica dataset: A digital replica of indoor spaces
J. Straub, T. Whelan, L. Ma, Y. Chen, E. Wijmans, S. Green, J. J. Engel, R. Mur-Artal, C. R., S. Verma, A. Clarkson, M. Yan, B. Budge, Y. Yan, X. Pan, J. Yon, Y. Zou, K. Leon, N. Carter, J. Briales, T. Gillingham, E. Mueggler, L. Pesqueira, M. Savva, D. Batra, H. M. Strasdat, R. D. Nardi, M. Goesele, S. Lovegrove, and R. Newcombe · 2019
Cited alongside, same era.
Ba-net: Dense bundle adjustment network
Chengzhou Tang and Ping Tan · 2019
Cited alongside, same era.
Scenecode: Monocular dense semantic reconstruction using learned encoded scene representations
Shuaifeng Zhi, Michael Bloesch, Stefan Leutenegger, and Andrew J Davison · 2019
Cited alongside, same era.
Implicit functions in feature space for 3d shape reconstruction and completion
Julian Chibane, Thiemo Alldieck, and Gerard Pons-Moll · 2020
Cited alongside, same era.
Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Zachary Teed and Jia Deng · 2021
Later among the works it cites.
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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Nerf–: Neural radiance fields without known camera parameters
Z. Wang, S. Wu, W. Xie, M. Chen, and V. A. Prisacariu · 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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iNeRF: Inverting neural radiance fields for pose estimation
L. Yen-Chen, P. Florence, J. T. Barron, A. Rodriguez, P. Isola, and T. Lin · 2021
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Deepfactors: Real-time probabilistic dense monocular slam
Jan Czarnowski, Tristan Laidlow, Ronald Clark, and Andrew J Davison · 2020
Cited alongside, same era.
Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
Cited alongside, same era.
Local implicit grid representations for 3d scenes
Chiyu Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, and Thomas Funkhouser · 2020
Cited alongside, same era.
Dist: Rendering deep implicit signed distance function with differentiable sphere tracing
Shaohui Liu, Yinda Zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, and Zhaopeng Cui · 2020
Cited alongside, same era.
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.
Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
Cited alongside, same era.
Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
Cited alongside, same era.
Wenjing Bian, Zirui Wang, Kejie Li, Jia-Wang Bian, and Victor Adrian Prisacariu · 2022
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Gaussian activated neural radiance fields for high fidelity reconstruction and pose estimation
Shin-Fang Chng, Sameera Ramasinghe, Jamie Sherrah, and Simon Lucey · 2022
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Orbeez-slam: A real-time monocular visual slam with orb features and nerf-realized mapping
Chi-Ming Chung, Yang-Che Tseng, Ya-Ching Hsu, Xiang-Qian Shi, Yun-Hung Hua, Jia-Fong Yeh, Wen-Chin Chen, Yi-Ting Chen, and Winston H Hsu · 2022
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Volumetric bundle adjustment for online photorealistic scene capture
Ronald Clark · 2022
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Improving neural implicit surfaces geometry with patch warping
François Darmon, Bénédicte Bascle, Jean-Clément Devaux, Pascal Monasse, and Mathieu Aubry · 2022
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Eslam: Efficient dense slam system based on hybrid representation of signed distance fields
Mohammad Mahdi Johari, Camilla Carta, and François Fleuret · 2022
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Tandem: Tracking and dense mapping in real-time using deep multi-view stereo
Lukas Koestler, Nan Yang, Niclas Zeller, and Daniel Cremers · 2022
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Meslam: Memory efficient slam based on neural fields
Evgenii Kruzhkov, Alena Savinykh, Pavel Karpyshev, Mikhail Kurenkov, Evgeny Yudin, Andrei Potapov, and Dzmitry Tsetserukou · 2022
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idf-slam: End-to-end rgb-d slam with neural implicit mapping and deep feature tracking
Yuhang Ming, Weicai Ye, and Andrew Calway · 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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isdf: Real-time neural signed distance fields for robot perception
Joseph Ortiz, Alexander Clegg, Jing Dong, Edgar Sucar, David Novotny, Michael Zollhoefer, and Mustafa Mukadam · 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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Scalable neural indoor scene rendering
Xiuchao Wu, Jiamin Xu, Zihan Zhu, Hujun Bao, Qixing Huang, James Tompkin, and Weiwei Xu · 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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Gmflow: Learning optical flow via global matching
Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, and Dacheng Tao · 2022
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Vox-fusion: Dense tracking and mapping with voxel-based neural implicit representation
Xingrui Yang, Hai Li, Hongjia Zhai, Yuhang Ming, Yuqian Liu, and Guofeng Zhang · 2022
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Monosdf: Exploring monocular geometric cues for neural implicit surface reconstruction
Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, and Andreas Geiger · 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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Dense rgb slam with neural implicit maps
Heng Li, Xiaodong Gu, Weihao Yuan, Luwei Yang, Zilong Dong, and Ping Tan · 2023
Closest in time.
Towards open world nerf-based slam
Daniil Lisus and Connor Holmes · 2023
Closest in time.