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We propose a new multi-instance dynamic RGB-D SLAM system using an object-level octree-based volumetric representation.
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2006
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A. J. Davison, N. D. Molton, I. Reid, and O. Stasse, “MonoSLAM: Real-Time Single Camera SLAM,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) , vol. 29, no. 6, pp. 1052–1067, 2007
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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 Conference on Intelligent Robots and Systems (IROS) , 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 (ECCV) , 2014, pp. 740–755
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R. A. Newcombe, D. Fox, and S. M. Seitz, “Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2015
2015
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T. Whelan, R. F. Salas-Moreno, B. Glocker, A. J. Davison, and S. Leutenegger, “ElasticFusion: Real-time dense SLAM and light source estimation,” International Journal of Robotics Research (IJRR) , vol. 35, no. 14, pp. 1697–1716, 2016
2016
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2016
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Y. Wu et al. , “Tensorpack,” https://github.com/tensorpack/ , 2016
2016
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J. Engel, V. Koltun, and D. Cremers, “Direct sparse odometry,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) , 2017
2017
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R. Scona, M. Jaimez, Y. R. Petillot, M. Fallon, and D. Cremers, “StaticFusion: Background reconstruction for dense rgb-d slam in dynamic environments,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 2018
2018
Closest in time.
D. Barnes, W. Maddern, G. Pascoe, and I. Posner, “Driven to distraction: Self-supervised distractor learning for robust monocular visual odometry in urban environments,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 2018
2018
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B. Bescós, J. M. Fácil, J. Civera, and J. Neira, “Dynaslam: Tracking, mapping and inpainting in dynamic scenes,” IEEE Robotics and Automation Letters , 2018
2018
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I. A. Bârsan, P. Liu, M. Pollefeys, and A. Geiger, “Robust dense mapping for large-scale dynamic environments,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 2018
2018
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M. Jaimez, C. Kerl, J. Gonzalez-Jimenez, and D. Cremers, “Fast odometry and scene flow from rgb-d cameras based on geometric clustering,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 2017
2017
Cited alongside, same era.
M. Rünz and L. Agapito, “Co-fusion: Real-time segmentation, tracking and fusion of multiple objects,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 2017
2017
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K. He, G. Gkioxari, P. Dollár, and R. Girshick, “Mask r-cnn,” in Proceedings of the International Conference on Computer Vision (ICCV) , 2017
2017
Cited alongside, same era.
T. Laidlow, M. Bloesch, W. Li, and S. Leutenegger, “Dense RGB-D-Inertial SLAM with map deformations,” in Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS) , 2017
2017
Cited alongside, same era.
2018
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J. McCormac, R. Clark, M. Bloesch, A. J. Davison, and S. Leutenegger, “Fusion ++
2018
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E. Vespa, N. Nikolov, M. Grimm, L. Nardi, P. H. Kelly, and S. Leutenegger, “Efficient octree-based volumetric SLAM supporting signed-distance and occupancy mapping,” IEEE Robotics and Automation Letters , 2018
2018
Closest in time.