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Recent advancements in RGB-only dense Simultaneous Localization and Mapping (SLAM) have predominantly utilized grid-based neural implicit encodings and/or struggle to efficiently realize global map and pose consistency.
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Zhu, Z., Peng, S., Larsson, V., Xu, W., Bao, H., Cui, Z., Oswald, M.R., Pollefeys, M.: Nice-slam: Neural implicit scalable encoding for slam. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12786–12796 (2022)
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Wang, H., Wang, J., Agapito, L.: 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 (CVPR). pp. 13293–13302 (June 2023)
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Xinyang, L., Yijin, L., Yanbin, T., Hujun, B., Guofeng, Z., Yinda, Z., Zhaopeng, C.: Multi-modal neural radiance field for monocular dense slam with a light-weight tof sensor. In: International Conference on Computer Vision (ICCV) (2023)
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Yugay, V., Li, Y., Gevers, T., Oswald, M.R.: Gaussian-slam: Photo-realistic dense slam with gaussian splatting (2023)
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Zhang, W., Sun, T., Wang, S., Cheng, Q., Haala, N.: Hi-slam: Monocular real-time dense mapping with hybrid implicit fields. IEEE Robotics and Automation Letters (2023)
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Zhang, Y., Tosi, F., Mattoccia, S., Poggi, M.: Go-slam: Global optimization for consistent 3d instant reconstruction. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 3727–3737 (2023)
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2024
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2024
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Tosi, F., Zhang, Y., Gong, Z., Sandström, E., Mattoccia, S., Oswald, M.R., Poggi, M.: How nerfs and 3d gaussian splatting are reshaping slam: a survey (2024)
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Zhou, H., Guo, Z., Liu, S., Zhang, L., Wang, Q., Ren, Y., Li, M.: Mod-slam: Monocular dense mapping for unbounded 3d scene reconstruction (2024)
2024
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