Fetching the paper…
Reading the bibliography…
In this paper, we introduce Hi-Map, a novel monocular dense mapping approach based on Neural Radiance Field (NeRF).
R. A. Newcombe, S. Izadi, O. Hilliges, D. Molyneaux, D. Kim, A. J. Davison, P. Kohli, J. Shotton, S. Hodges, and A. W. Fitzgibbon, “Kinectfusion: Real-time dense surface mapping and tracking,” 2011 10th IEEE International Symposium on Mixed and Augmented Reality , pp. 127–136, 2011. [Online]. Available: https://api.semanticscholar.org/CorpusID:11830123
2011
Earlier work this paper cites.
J. Sturm, N. Engelhard, F. Endres, W. Burgard, and D. Cremers, “A benchmark for the evaluation of rgb-d slam systems,” in Proc. of the International Conference on Intelligent Robot Systems (IROS) , Oct. 2012
2012
Earlier work this paper cites.
A. Hornung, K. M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, “Octomap: An efficient probabilistic 3d mapping framework based on octrees,” Autonomous robots , vol. 34, pp. 189–206, 2013
2013
Earlier work this paper cites.
M. Nießner, M. Zollhöfer, S. Izadi, and M. Stamminger, “Real-time 3d reconstruction at scale using voxel hashing,” ACM Transactions on Graphics (ToG) , vol. 32, no. 6, pp. 1–11, 2013
2013
Earlier work this paper cites.
K. Schauwecker and A. Zell, “Robust and efficient volumetric occupancy mapping with an application to stereo vision,” in 2014 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2014, pp. 6102–6107
2014
Earlier work this paper cites.
T. Whelan, M. Kaess, H. Johannsson, M. Fallon, J. J. Leonard, and J. McDonald, “Real-time large-scale dense rgb-d slam with volumetric fusion,” The International Journal of Robotics Research , vol. 34, no. 4-5, pp. 598–626, 2015
2015
Earlier work this paper cites.
A. Dai, M. Nießner, M. Zollhöfer, S. Izadi, and C. Theobalt, “Bundlefusion,” ACM Transactions on Graphics (TOG) , vol. 36, pp. 1 – 18, 2016. [Online]. Available: https://api.semanticscholar.org/CorpusID:32286806
2016
Earlier work this paper cites.
T. Whelan, R. F. Salas-Moreno, B. Glocker, A. J. Davison, and S. Leutenegger, “Elasticfusion: Real-time dense slam and light source estimation,” The International Journal of Robotics Research , vol. 35, pp. 1697 – 1716, 2016. [Online]. Available: https://api.semanticscholar.org/CorpusID:21124365
2016
Earlier work this paper cites.
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, p. 1, 2017
2017
Earlier work this paper cites.
Z. Yan, M. Ye, and L. Ren, “Dense visual slam with probabilistic surfel map,” IEEE Transactions on Visualization and Computer Graphics , vol. 23, pp. 2389–2398, 2017. [Online]. Available: https://api.semanticscholar.org/CorpusID:8013890
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
J. Du, W. Sheng, and M. Liu, “A human–robot collaborative system for robust three-dimensional mapping,” IEEE/ASME Transactions on Mechatronics , vol. 23, no. 5, pp. 2358–2368, 2018
2018
Earlier work this paper cites.
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 , vol. 3, no. 2, pp. 1144–1151, 2018
2018
Earlier work this paper cites.
K. Wang, F. Gao, and S. Shen, “Real-time scalable dense surfel mapping,” in 2019 International conference on robotics and automation (ICRA) . IEEE, 2019, pp. 6919–6925
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
T. Schöps, T. Sattler, and M. Pollefeys, “Bad slam: Bundle adjusted direct rgb-d slam,” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pp. 134–144, 2019. [Online]. Available: https://api.semanticscholar.org/CorpusID:196201321
2019
Cited alongside, same era.
J. Xiao, P. Wang, H. Lu, and H. Zhang, “A three-dimensional mapping and virtual reality-based human–robot interaction for collaborative space exploration,” International Journal of Advanced Robotic Systems , vol. 17, no. 3, p. 1729881420925293, 2020
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,” Communications of the ACM , vol. 65, no. 1, pp. 99–106, 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 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021 . IEEE, 2021, pp. 6209–6218. [Online]. Available: https://doi.org/10.1109/ICCV48922.2021.00617
X. Zhong, Y. Pan, J. Behley, and C. Stachniss, “Shine-mapping: Large-scale 3d mapping using sparse hierarchical implicit neural representations,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 8371–8377
2023
Later among the works it cites.
2023
Later among the works it cites.
X. Liu, Y. Li, Y. Teng, H. Bao, G. Zhang, Y. Zhang, and Z. Cui, “Multi-modal neural radiance field for monocular dense slam with a light-weight tof sensor,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 1–11
2023
Later among the works it cites.
A. Rosinol, J. J. Leonard, and L. Carlone, “Nerf-slam: Real-time dense monocular slam with neural radiance fields,” in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2023, pp. 3437–3444
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2021
Cited alongside, same era.
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 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022 . IEEE, 2022, pp. 12 776–12 786. [Online]. Available: https://doi.org/10.1109/CVPR52688.2022.01245
2022
Cited alongside, same era.
X. Yang, H. Li, H. Zhai, Y. Ming, Y. Liu, and G. Zhang, “Vox-fusion: Dense tracking and mapping with voxel-based neural implicit representation,” in 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) . IEEE, 2022, pp. 499–507
2022
Cited alongside, same era.
2022
Cited alongside, same era.
H. Li, X. Gu, W. Yuan, Z. Dong, P. Tan, et al. , “Dense rgb slam with neural implicit maps,” in The Eleventh International Conference on Learning Representations , 2022
2022
Cited alongside, same era.
A. Chen, Z. Xu, A. Geiger, J. Yu, and H. Su, “Tensorf: Tensorial radiance fields,” in European Conference on Computer Vision . Springer, 2022, pp. 333–350
2022
Cited alongside, same era.
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 , 2022, pp. 6290–6301
2022
Cited alongside, same era.
R. Or-El, X. Luo, M. Shan, E. Shechtman, J. J. Park, and I. Kemelmacher-Shlizerman, “Stylesdf: High-resolution 3d-consistent image and geometry generation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 13 503–13 513
2022
Cited alongside, same era.
H. Wang, J. Wang, and L. Agapito, “Co-slam: Joint coordinate and sparse parametric encodings for neural real-time slam,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 13 293–13 302
2023
Cited alongside, same era.
2023
Later among the works it cites.
C.-M. Chung, Y.-C. Tseng, Y.-C. Hsu, X.-Q. Shi, Y.-H. Hua, J.-F. Yeh, W.-C. Chen, Y.-T. Chen, and W. H. Hsu, “Orbeez-slam: A real-time monocular visual slam with orb features and nerf-realized mapping,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 9400–9406
2023
Later among the works it cites.
Y. Zhang, F. Tosi, S. Mattoccia, and M. Poggi, “Go-slam: Global optimization for consistent 3d instant reconstruction,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 3727–3737
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
H. Matsuki, E. Sucar, T. Laidow, K. Wada, R. Scona, and A. J. Davison, “imode: Real-time incremental monocular dense mapping using neural field,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 4171–4177
2023
Later among the works it cites.
J. Deng, Q. Wu, X. Chen, S. Xia, Z. Sun, G. Liu, W. Yu, and L. Pei, “Nerf-loam: Neural implicit representation for large-scale incremental lidar odometry and mapping,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 8218–8227
2023
Later among the works it cites.
S. Liu and J. Zhu, “Efficient map fusion for multiple implicit slam agents,” IEEE Transactions on Intelligent Vehicles , 2023
2023
Later among the works it cites.
B. Xiang, Y. Sun, Z. Xie, X. Yang, and Y. Wang, “Nisb-map: Scalable mapping with neural implicit spatial block,” IEEE Robotics and Automation Letters , 2023
2023
Later among the works it cites.
J. Hu, M. Mao, H. Bao, G. Zhang, and Z. Cui, “Cp-slam: Collaborative neural point-based slam system,” in Thirty-seventh Conference on Neural Information Processing Systems , 2023
2023
Later among the works it cites.