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We provide an open-source C++ library for real-time metric-semantic visual-inertial Simultaneous Localization And Mapping (SLAM).
B. Horn, “Closed-form solution of absolute orientation using unit quaternions,” J. Opt. Soc. Amer. , vol. 4, no. 4, pp. 629–642, Apr 1987
1987
Earlier work this paper cites.
W. Lorensen and H. Cline, “Marching cubes: A high resolution 3d surface construction algorithm,” in SIGGRAPH , 1987, pp. 163–169
1987
Earlier work this paper cites.
P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Machine Intell. , vol. 14, no. 2, 1992
1992
Earlier work this paper cites.
J. Shi and C. Tomasi, “Good features to track,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 1994, pp. 593–600
1994
Earlier work this paper cites.
J. Bouguet, “Pyramidal implementation of the Lucas Kanade feature tracker,” 2000
2000
Earlier work this paper cites.
D. Nistér, “An efficient solution to the five-point relative pose problem,” IEEE Trans. Pattern Anal. Machine Intell. , vol. 26, no. 6, pp. 756–770, 2004
2004
Earlier work this paper cites.
R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision , 2nd ed. Cambridge University Press, 2004
2004
Earlier work this paper cites.
A. Mourikis and S. Roumeliotis, “A multi-state constraint Kalman filter for vision-aided inertial navigation,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , April 2007, pp. 3565–3572
2007
Earlier work this paper cites.
G. J. Brostow, J. Shotton, J. Fauqueur, and R. Cipolla, “Segmentation and recognition using structure from motion point clouds,” in European Conf. on Computer Vision (ECCV) , 2008, pp. 44–57
2008
Earlier work this paper cites.
H. H. Hirschmüller, “Stereo processing by semiglobal matching and mutual information,” IEEE Trans. Pattern Anal. Machine Intell. , vol. 30, no. 2, pp. 328–341, 2008
2008
Earlier work this paper cites.
M. Quigley, K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A. Y. Ng, “Ros: an open-source robot operating system,” in ICRA workshop on open source software , vol. 3, no. 3.2. Kobe, Japan, 2009, p. 5
2009
Earlier work this paper cites.
O. Enqvist, F. Kahl, and C. Olsson, “Non-sequential structure from motion,” in Intl. Conf. on Computer Vision (ICCV) , 2011, pp. 264–271
2011
Earlier work this paper cites.
S. Y.-Z. Bao and S. Savarese, “Semantic structure from motion,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2011
2011
Earlier work this paper cites.
L. Kneip, M. Chli, and R. Siegwart, “Robust real-time visual odometry with a single camera and an IMU,” in British Machine Vision Conf. (BMVC) , 2011, pp. 16.1–16.11
2011
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” in Advances in Neural Information Processing Systems (NIPS) , ser. NIPS’12, 2012, pp. 1097–1105
2012
Earlier work this paper cites.
M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. Leonard, and F. Dellaert, “iSAM2: Incremental smoothing and mapping using the Bayes tree,” Intl. J. of Robotics Research , vol. 31, pp. 217–236, Feb 2012
2012
Earlier work this paper cites.
F. Dellaert, “Factor graphs and GTSAM: A hands-on introduction,” Georgia Institute of Technology, Tech. Rep. GT-RIM-CP&R-2012-002, September 2012
2012
Earlier work this paper cites.
D. Gálvez-López and J. D. Tardós, “Bags of binary words for fast place recognition in image sequences,” IEEE Transactions on Robotics , vol. 28, no. 5, pp. 1188–1197, October 2012
2012
Earlier work this paper cites.
R. F. Salas-Moreno, R. A. Newcombe, H. Strasdat, P. H. J. Kelly, and A. J. Davison, “SLAM++: Simultaneous localisation and mapping at the level of objects,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2013
2013
Earlier work this paper cites.
M. Keller, D. Lefloch, M. Lambers, S. Izadi, T. Weyrich, and A. Kolb, “Real-time 3d reconstruction in dynamic scenes using point-based fusion,” in Intl. Conf. on 3D Vision (3DV) , 2013
2013
Earlier work this paper cites.
S. Leutenegger, P. Furgale, V. Rabaud, M. Chli, K. Konolige, and R. Siegwart, “Keyframe-based visual-inertial slam using nonlinear optimization,” in Robotics: Science and Systems (RSS) , 2013
2013
Earlier work this paper cites.
L. Carlone, Z. Kira, C. Beall, V. Indelman, and F. Dellaert, “Eliminating conditionally independent sets in factor graphs: A unifying perspective based on smart factors,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2014, pp. 4290–4297
2014
Earlier work this paper cites.
S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards realtime object detection with region proposal networks,” in Advances in Neural Information Processing Systems (NIPS) , 2015, pp. 91–99
2015
Earlier work this paper cites.
T. Whelan, S. Leutenegger, R. Salas-Moreno, B. Glocker, and A. Davison, “ElasticFusion: Dense SLAM without a pose graph,” in Robotics: Science and Systems (RSS) , 2015
2015
Earlier work this paper cites.
R. Mur-Artal, J. Montiel, and J. Tardós, “ORB-SLAM: A versatile and accurate monocular SLAM system,” IEEE Trans. Robotics , vol. 31, no. 5, pp. 1147–1163, 2015
2015
Earlier work this paper cites.
K. Tateno, F. Tombari, and N. Navab, “Real-time and scalable incremental segmentation on dense slam,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) , 2015, pp. 4465–4472
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
B. Pattabiraman, M. M. A. Patwary, A. H. Gebremedhin, W. K. Liao, and A. Choudhary, “Fast algorithms for the maximum clique problem on massive graphs with applications to overlapping community detection,” Internet Mathematics , vol. 11, no. 4-5, pp. 421–448, 2015
2015
Cited alongside, same era.
M. Bloesch, S. Omari, M. Hutter, and R. Siegwart, “Robust visual inertial odometry using a direct EKF-based approach,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) . IEEE, 2015
2015
Cited alongside, same era.
C. Forster, L. Carlone, F. Dellaert, and D. Scaramuzza, “IMU preintegration on manifold for efficient visual-inertial maximum-a-posteriori estimation,” in Robotics: Science and Systems (RSS) , 2015, accepted as oral presentation (acceptance rate 4 % 4\% ) (pdf) (video) (supplemental material: (pdf) )
2015
Cited alongside, same era.
D. Wolf, J. Prankl, and M. Vincze, “Enhancing semantic segmentation for robotics: The power of 3-d entangled forests,” IEEE Robotics and Automation Letters , vol. 1, no. 1, pp. 49–56, 2015
J. Engel, V. Koltun, and D. Cremers, “Direct sparse odometry,” IEEE Trans. Pattern Anal. Machine Intell. , 2018
2018
Later among the works it cites.
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
Later among the works it cites.
T. Schneider, M. T. Dymczyk, M. Fehr, K. Egger, S. Lynen, I. Gilitschenski, and R. Siegwart, “maplab: An open framework for research in visual-inertial mapping and localization,” IEEE Robotics and Automation Letters , 2018
2018
Later among the works it cites.
M. Runz, M. Buffier, and L. Agapito, “Maskfusion: Real-time recognition, tracking and reconstruction of multiple moving objects,” in IEEE International Symposium on Mixed and Augmented Reality (ISMAR) . IEEE, 2018, pp. 10–20
2018
Later among the works it cites.
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alphaXiv is searching for related work…
2015
Cited alongside, same era.
2016
Cited alongside, same era.
M. Burri, J. Nikolic, P. Gohl, T. Schneider, J. Rehder, S. Omari, M. Achtelik, and R. Siegwart, “The EuRoC micro aerial vehicle datasets,” Intl. J. of Robotics Research , 2016
2016
Cited alongside, same era.
C. Li, H. Xiao, K. Tateno, F. Tombari, N. Navab, and G. D. Hager, “Incremental scene understanding on dense SLAM,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) , 2016, pp. 574–581
2016
Cited alongside, same era.
L. Teixeira and M. Chli, “Real-time mesh-based scene estimation for aerial inspection,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) . IEEE, 2016, pp. 4863–4869
2016
Cited alongside, same era.
2016
Cited alongside, same era.
T. Schöps, J. L. Schönberger, S. Galliani, T. Sattler, K. Schindler, M. Pollefeys, and A. Geiger, “A multi-view stereo benchmark with high-resolution images and multi-camera videos,” in Conference on Computer Vision and Pattern Recognition (CVPR) , 2017
2017
Cited alongside, same era.
A. Garcia-Garcia, S. Orts-Escolano, S. Oprea, V. Villena-Martinez, and J. García-Rodríguez, “A review on deep learning techniques applied to semantic segmentation,” ArXiv Preprint: 1704.06857 , 2017
2017
Cited alongside, same era.
J. Redmon and A. Farhadi, “YOLO9000: Better, faster, stronger,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2017, pp. 6517–6525
2017
Cited alongside, same era.
R. Dubé, A. Cramariuc, D. Dugas, J. Nieto, R. Siegwart, and C. Cadena, “SegMap: 3d segment mapping using data-driven descriptors,” in Robotics: Science and Systems (RSS) , 2018
2018
Later among the works it cites.
J. McCormac, R. Clark, M. Bloesch, A. J. Davison, and S. Leutenegger, “Fusion++: Volumetric object-level SLAM,” in Intl. Conf. on 3D Vision (3DV) , 2018, pp. 32–41
2018
Later among the works it cites.
J. Wald, K. Tateno, J. Sturm, N. Navab, and F. Tombari, “Real-time fully incremental scene understanding on mobile platforms,” IEEE Robotics and Automation Letters , vol. 3, no. 4, pp. 3402–3409, 2018
2018
Later among the works it cites.
K.-N. Lianos, J. L. Schönberger, M. Pollefeys, and T. Sattler, “Vso: Visual semantic odometry,” in European Conf. on Computer Vision (ECCV) , 2018, pp. 246–263
2018
Later among the works it cites.
J. G. Mangelson, D. Dominic, R. M. Eustice, and R. Vasudevan, “Pairwise consistent measurement set maximization for robust multi-robot map merging,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2018, pp. 2916–2923
2018
Later among the works it cites.
G. Yang, H. Zhao, J. Shi, Z. Deng, and J. Jia, “Segstereo: Exploiting semantic information for disparity estimation,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 636–651
2018
Later among the works it cites.
2018
Later among the works it cites.
J. Delmerico and D. Scaramuzza, “A benchmark comparison of monocular visual-inertial odometry algorithms for flying robots,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 2502–2509
2018
Later among the works it cites.
A. Rosinol, “Densifying Sparse VIO: a Mesh-based approach using Structural Regularities.” Master’s thesis, ETH Zurich, 2018
2018
Later among the works it cites.
M. Grinvald, F. Furrer, T. Novkovic, J. J. Chung, C. Cadena, R. Siegwart, and J. Nieto, “Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery,” IEEE Robotics and Automation Letters , vol. 4, no. 3, pp. 3037–3044, 2019
2019
Closest in time.
L. Zheng, C. Zhu, J. Zhang, H. Zhao, H. Huang, M. Niessner, and K. Xu, “Active scene understanding via online semantic reconstruction,” arXiv preprint:1906.07409 , 2019
2019
Closest in time.
W. Guerra, E. Tal, V. Murali, G. Ryou, and S. Karaman, “FlightGoggles: Photorealistic sensor simulation for perception-driven robotics using photogrammetry and virtual reality,” in arXiv preprint: 1905.11377 , 2019
2019
Closest in time.
T. Qin, J. Pan, S. Cao, and S. Shen, “A general optimization-based framework for local odometry estimation with multiple sensors,” arXiv preprint: 1901.03638 , 2019
2019
Closest in time.
B. Xu, W. Li, D. Tzoumanikas, M. Bloesch, A. Davison, and S. Leutenegger, “MID-Fusion: Octree-based object-level multi-instance dynamic slam,” 2019, pp. 5231–5237
2019
Closest in time.
G. Narita, T. Seno, T. Ishikawa, and Y. Kaji, “Panopticfusion: Online volumetric semantic mapping at the level of stuff and things,” arxiv preprint: 1903.01177 , 2019
2019
Closest in time.
2019
Closest in time.
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall, “SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences,” in Intl. Conf. on Computer Vision (ICCV) , 2019
2019
Closest in time.
F. Dellaert et al., “Georgia Tech Smoothing And Mapping (GTSAM),” https://gtsam.org/ , 2019
2019
Closest in time.
2019
Closest in time.
2019
Closest in time.
L. Zhang, X. Li, A. Arnab, K. Yang, Y. Tong, and P. H. Torr, “Dual graph convolutional network for semantic segmentation,” in British Machine Vision Conference , 2019
2019
Closest in time.
2019
Closest in time.
Cloudcompare.org, “CloudCompare - open source project,” https://www.cloudcompare.org , 2019
2019
Closest in time.