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In recent years, there have been significant advancements in 3D reconstruction and dense RGB-D SLAM systems.
G. Klein and D. Murray, “Parallel tracking and mapping for small ar workspaces,” in Proceedings of the IEEE/ACM International Conference on Symposium on Mixed and Augmented Reality , 2007, pp. 225–234
2007
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R. A. Newcombe, S. J. Lovegrove, and A. J. Davison, “Dtam: Dense tracking and mapping in real-time,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2011, pp. 2320–2327
2011
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S. Izadi, D. Kim, O. Hilliges, D. Molyneaux, R. Newcombe, P. Kohli, J. Shotton, S. Hodges, D. Freeman, A. Davison et al. , “Kinectfusion: real-time 3d reconstruction and interaction using a moving depth camera,” in Proceedings of the 24th annual ACM symposium on User interface software and technology , 2011, pp. 559–568
2011
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J. Sturm, N. Engelhard, F. Endres, W. Burgard, and D. Cremers, “A benchmark for the evaluation of rgb-d slam systems,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems , 2012, pp. 573–580
2012
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T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in Proceedings of the European Conference on Computer Vision , 2014, pp. 740–755
2014
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O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in Proceeding of the International Conference in Medical Image Computing and Computer-Assisted Intervention , 2015, pp. 234–241
2015
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D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” in Proceedings of the International Conference on Learning Representations , 2015
2015
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T. Whelan, S. Leutenegger, R. Salas-Moreno, B. Glocker, and A. Davison, “Elasticfusion: Dense slam without a pose graph.” Robotics: Science and Systems, 2015
2015
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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , June 2016
2016
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R. Mur-Artal and J. D. Tardós, “Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras,” IEEE Transactions on Robotics , vol. 33, no. 5, pp. 1255–1262, 2017
2017
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B. Ummenhofer, H. Zhou, J. Uhrig, N. Mayer, E. Ilg, A. Dosovitskiy, and T. Brox, “Demon: Depth and motion network for learning monocular stereo,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , July 2017
2017
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A. Dai, M. Nießner, M. Zollhöfer, S. Izadi, and C. Theobalt, “Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface reintegration,” ACM Transactions on Graphics (ToG) , vol. 36, no. 4, 2017
2017
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A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Niessner, “Scannet: Richly-annotated 3d reconstructions of indoor scenes,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , July 2017
2017
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M. Bloesch, J. Czarnowski, R. Clark, S. Leutenegger, and A. J. Davison, “Codeslam—learning a compact, optimisable representation for dense visual slam,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 2560–2568
2018
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T. Qin, P. Li, and S. Shen, “Vins-mono: A robust and versatile monocular visual-inertial state estimator,” IEEE Transactions on Robotics , vol. 34, no. 4, pp. 1004–1020, 2018
2018
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C. Tang and P. Tan, “Ba-net: Dense bundle adjustment network,” in Proceedings of the International Conference on Learning Representations , September 2018
2018
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D. DeTone, T. Malisiewicz, and A. Rabinovich, “Superpoint: Self-supervised interest point detection and description,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops , June 2018
2018
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T. Schops, T. Sattler, and M. Pollefeys, “Bad slam: Bundle adjusted direct rgb-d slam,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2019, pp. 134–144
2019
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S. Zhi, M. Bloesch, S. Leutenegger, and A. J. Davison, “Scenecode: Monocular dense semantic reconstruction using learned encoded scene representations,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2019, pp. 11 776–11 785
2019
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2019
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X. Liu, Z. Lin, Y. Niu, Z. Lyu, Q. Xu, B. Cui, and T. Deng, “A multi-uav cooperative search system design based on man-in-the-loop,” in 2020 3rd International Conference on Unmanned Systems (ICUS) . IEEE, 2020, pp. 757–762
2020
Cited alongside, same era.
T. Deng, “Research on aerial robot based on visual servo,” in Journal of Physics: Conference Series , vol. 1678, no. 1. IOP Publishing, 2020, p. 012007
2020
Cited alongside, same era.
B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng, “Nerf: Representing scenes as neural radiance fields for view synthesis,” in European Conference on Computer Vision , 2020
2020
Cited alongside, same era.
X. Cheng, P. Wang, and R. Yang, “Learning depth with convolutional spatial propagation network,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 42, no. 10, pp. 2361–2379, 2020
2020
Cited alongside, same era.
J. Huang, S.-S. Huang, H. Song, and S.-M. Hu, “Di-fusion: Online implicit 3d reconstruction with deep priors,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 8932–8941
2021
Later among the works it cites.
H. Xie, T. Deng, J. Wang, and W. Chen, “Robust incremental long-term visual topological localization in changing environments,” IEEE Transactions on Instrumentation and Measurement , vol. 72, pp. 1–14, 2022
2022
Later among the works it cites.
M. U. M. Bhutta, M. Kuse, R. Fan, Y. Liu, and M. Liu, “Loop-box: Multiagent direct slam triggered by single loop closure for large-scale mapping,” IEEE Transactions on Cybernetics , vol. 52, no. 6, pp. 5088–5097, 2022
2022
Later among the works it cites.
Z. Zhu, S. Peng, V. Larsson, W. Xu, H. Bao, Z. Cui, M. R. Oswald, and M. Pollefeys, “Nice-slam: Neural implicit scalable encoding for slam,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , June 2022, pp. 12 786–12 796
2022
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J. Park, K. Joo, Z. Hu, C.-K. Liu, and I. So Kweon, “Non-local spatial propagation network for depth completion,” in Proceedings of the European Conference on Computer Vision , 2020, pp. 120–136
2020
Cited alongside, same era.
M. Tancik, P. Srinivasan, B. Mildenhall, and Fridovich-Keil, “Fourier features let networks learn high frequency functions in low dimensional domains,” in Advances in Neural Information Processing Systems , vol. 33, 2020, pp. 7537–7547
2020
Cited alongside, same era.
A. Gropp, L. Yariv, N. Haim, M. Atzmon, and Y. Lipman, “Implicit geometric regularization for learning shapes,” in Proceeding of the International Conference on Machine Learning , 2020, pp. 3789–3799
2020
Cited alongside, same era.
H. Matsuki, R. Scona, J. Czarnowski, and A. J. Davison, “Codemapping: Real-time dense mapping for sparse slam using compact scene representations,” IEEE Robotics and Automation Letters , vol. 6, no. 4, pp. 7105–7112, 2021
2021
Cited alongside, same era.
Z. Teed and J. Deng, “Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras,” Advances in neural information processing systems , vol. 34, pp. 16 558–16 569, 2021
2021
Cited alongside, same era.
E. Sucar, S. Liu, J. Ortiz, and A. J. Davison, “imap: Implicit mapping and positioning in real-time,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , October 2021, pp. 6229–6238
2021
Cited alongside, same era.
M. Oechsle, S. Peng, and A. Geiger, “Unisurf: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , October 2021, pp. 5589–5599
2021
Cited alongside, same era.
P. Wang, L. Liu, Y. Liu, C. Theobalt, T. Komura, and W. Wang, “Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction,” in Advances in Neural Information Processing Systems , vol. 34, 2021, pp. 27 171–27 183
2021
Cited alongside, same era.
Later among the works it cites.
X. Gao, X. Liu, Z. Cao, M. Tan, and J. Yu, “Dynamic rigid bodies mining and motion estimation based on monocular camera,” IEEE Transactions on Cybernetics , pp. 1–12, 2022
2022
Later among the works it cites.
R. Fan, U. Ozgunalp, Y. Wang, M. Liu, and I. Pitas, “Rethinking road surface 3-d reconstruction and pothole detection: From perspective transformation to disparity map segmentation,” IEEE Transactions on Cybernetics , vol. 52, no. 7, pp. 5799–5808, 2022
2022
Later among the works it cites.
D. Azinović, R. Martin-Brualla, D. B. Goldman, M. Nießner, and J. Thies, “Neural rgb-d surface reconstruction,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , June 2022, pp. 6290–6301
2022
Later among the works it cites.
B. Roessle, J. T. Barron, B. Mildenhall, P. P. Srinivasan, and M. Nießner, “Dense depth priors for neural radiance fields from sparse input views,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , June 2022, pp. 12 892–12 901
2022
Later among the works it cites.
T. Deng, H. Xie, J. Wang, and W. Chen, “Long-term visual simultaneous localization and mapping: Using a bayesian persistence filter-based global map prediction,” IEEE Robotics & Automation Magazine , vol. 30, no. 1, pp. 36–49, 2023
2023
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2023
Later among the works it cites.
2023
Later among the works it cites.
T. Deng, H. Xie, J. Wang, and W. Chen, “Long-term visual simultaneous localization and mapping: Using a bayesian persistence filter-based global map prediction,” IEEE Robotics & Automation Magazine , vol. 30, no. 1, pp. 36–49, 2023
2023
Later among the works it cites.
S. Zhao, X. Wang, D. Zhang, G. Zhang, Z. Wang, and H. Liu, “Fm-3dfr: Facial manipulation-based 3-d face reconstruction,” IEEE Transactions on Cybernetics , pp. 1–10, 2023
2023
Later among the works it cites.
C. Xia, Y. Shen, Y. Yang, X. Deng, S. Chen, J. Xin, and N. Zheng, “Onboard sensors-based self-localization for autonomous vehicle with hierarchical map,” IEEE Transactions on Cybernetics , vol. 53, no. 7, pp. 4218–4231, 2023
2023
Later among the works it cites.
——, “Angular tracking consistency guided fast feature association for visual-inertial slam,” IEEE Transactions on Instrumentation and Measurement , 2024
2024
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2024
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2024
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