Fetching the paper…
Reading the bibliography…
3D Gaussian Splatting has emerged as a powerful representation of geometry and appearance for RGB-only dense Simultaneous Localization and Mapping (SLAM), as it provides a compact dense map representation while enabling efficient and high-quality map rendering.
Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. ACM siggraph computer graphics
1987
Earlier work this paper cites.
Curless, B., Levoy, M.: Volumetric method for building complex models from range images. In: SIGGRAPH Conference on Computer Graphics. ACM (1996)
1996
Earlier work this paper cites.
Zwicker, M., Pfister, H., Van Baar, J., Gross, M.: Surface splatting. In: Proceedings of the 28th annual conference on Computer graphics and interactive techniques. pp. 371–378 (2001)
2001
Earlier work this paper cites.
Bosse, M., Newman, P., Leonard, J., Soika, M., Feiten, W., Teller, S.: An atlas framework for scalable mapping. In: 2003 IEEE International Conference on Robotics and Automation (Cat. No. 03CH37422). vol. 2, pp. 1899–1906. IEEE (2003)
2003
Earlier work this paper cites.
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing
2004
Earlier work this paper cites.
Newcombe, R.A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A.J., Kohli, P., Shotton, J., Hodges, S., Fitzgibbon, A.W.: Kinectfusion: Real-time dense surface mapping and tracking. In: ISMAR. vol. 11, pp. 127–136 (2011)
2011
Earlier work this paper cites.
Endres, F., Hess, J., Engelhard, N., Sturm, J., Cremers, D., Burgard, W.: An evaluation of the rgb-d slam system. In: 2012 IEEE international conference on robotics and automation. pp. 1691–1696. IEEE (2012)
2012
Earlier work this paper cites.
Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: Rgb-d mapping: Using kinect-style depth cameras for dense 3d modeling of indoor environments. The international journal of Robotics Research
2012
Earlier work this paper cites.
Sturm, J., Engelhard, N., Endres, F., Burgard, W., Cremers, D.: A benchmark for the evaluation of RGB-D SLAM systems. In: International Conference on Intelligent Robots and Systems (IROS). IEEE/RSJ (2012). https://doi.org/10.1109/IROS.2012.6385773,
2012
Earlier work this paper cites.
Chen, J., Bautembach, D., Izadi, S.: Scalable real-time volumetric surface reconstruction. ACM Transactions on Graphics (ToG)
2013
Earlier work this paper cites.
Henry, P., Fox, D., Bhowmik, A., Mongia, R.: Patch volumes: Segmentation-based consistent mapping with rgb-d cameras. In: 2013 International Conference on 3D Vision-3DV 2013. pp. 398–405. IEEE (2013)
2013
Earlier work this paper cites.
Keller, M., Lefloch, D., Lambers, M., Izadi, S., Weyrich, T., Kolb, A.: Real-time 3d reconstruction in dynamic scenes using point-based fusion. In: International Conference on 3D Vision (3DV). pp. 1–8. IEEE (2013)
2013
Earlier work this paper cites.
Kerl, C., Sturm, J., Cremers, D.: Dense visual slam for rgb-d cameras. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. pp. 2100–2106. IEEE (2013)
2013
Earlier work this paper cites.
Nießner, M., Zollhöfer, M., Izadi, S., Stamminger, M.: Real-time 3d reconstruction at scale using voxel hashing. ACM Transactions on Graphics (TOG)
2013
Earlier work this paper cites.
Steinbrucker, F., Kerl, C., Cremers, D.: Large-scale multi-resolution surface reconstruction from rgb-d sequences. In: IEEE International Conference on Computer Vision. pp. 3264–3271 (2013)
2013
Earlier work this paper cites.
Engel, J., Schöps, T., Cremers, D.: Lsd-slam: Large-scale direct monocular slam. In: European conference on computer vision. pp. 834–849. Springer (2014)
2014
Earlier work this paper cites.
Maier, R., Sturm, J., Cremers, D.: Submap-based bundle adjustment for 3d reconstruction from rgb-d data. In: Pattern Recognition: 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014, Proceedings 36. pp. 54–65. Springer (2014)
2014
Earlier work this paper cites.
Stückler, J., Behnke, S.: Multi-resolution surfel maps for efficient dense 3d modeling and tracking. Journal of Visual Communication and Image Representation
2014
Earlier work this paper cites.
Choi, S., Zhou, Q.Y., Koltun, V.: Robust reconstruction of indoor scenes. In: IEEE Conference on Computer Vision and Pattern Recognition. pp. 5556–5565 (2015)
2015
Earlier work this paper cites.
Fioraio, N., Taylor, J., Fitzgibbon, A., Di Stefano, L., Izadi, S.: Large-scale and drift-free surface reconstruction using online subvolume registration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 4475–4483 (2015)
2015
Earlier work this paper cites.
Kähler, O., Prisacariu, V.A., Ren, C.Y., Sun, X., Torr, P.H.S., Murray, D.W.: Very high frame rate volumetric integration of depth images on mobile devices. IEEE Trans. Vis. Comput. Graph
2015
Earlier work this paper cites.
Whelan, T., Leutenegger, S., Salas-Moreno, R., Glocker, B., Davison, A.: Elasticfusion: Dense slam without a pose graph. In: Robotics: Science and Systems (RSS) (2015)
2015
Earlier work this paper cites.
Kähler, O., Prisacariu, V.A., Murray, D.W.: Real-time large-scale dense 3d reconstruction with loop closure. In: Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII 14. pp. 500–516. Springer (2016)
2016
Earlier work this paper cites.
Wang, H., Wang, J., Liang, W.: Online reconstruction of indoor scenes from rgb-d streams. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3271–3279 (2016)
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
Dai, A., Nießner, M., Zollhöfer, M., Izadi, S., Theobalt, C.: Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface reintegration. ACM Transactions on Graphics (ToG)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
Marniok, N., Johannsen, O., Goldluecke, B.: An efficient octree design for local variational range image fusion. In: German Conference on Pattern Recognition (GCPR). pp. 401–412. Springer (2017)
2017
Earlier work this paper cites.
Oleynikova, H., Taylor, Z., Fehr, M., Siegwart, R., Nieto, J.I.: Voxblox: Incremental 3d euclidean signed distance fields for on-board MAV planning. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017, Vancouver, BC, Canada, September 24-28, 2017. pp. 1366–1373. IEEE (2017). https://doi.org/10.1109/IROS.2017.8202315,
2017
Cited alongside, same era.
Yan, Z., Ye, M., Ren, L.: Dense visual slam with probabilistic surfel map. IEEE transactions on visualization and computer graphics
2017
Cited alongside, same era.
Cao, Y.P., Kobbelt, L., Hu, S.M.: Real-time high-accuracy three-dimensional reconstruction with consumer rgb-d cameras. ACM Transactions on Graphics (TOG)
2018
Cited alongside, same era.
Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: IEEE conference on computer vision and pattern recognition. pp. 586–595 (2018)
2018
Cited alongside, same era.
2022
Later among the works it cites.
Hu, J., Mao, M., Bao, H., Zhang, G., Cui, Z.: 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.
2023
Later among the works it cites.
2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Reijgwart, V., Millane, A., Oleynikova, H., Siegwart, R., Cadena, C., Nieto, J.: Voxgraph: Globally consistent, volumetric mapping using signed distance function submaps. IEEE Robotics and Automation Letters
2019
Cited alongside, same era.
Schops, T., Sattler, T., Pollefeys, M.: BAD SLAM: Bundle adjusted direct RGB-D SLAM. In: CVF/IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Liu, L., Gu, J., Zaw Lin, K., Chua, T.S., Theobalt, C.: Neural sparse voxel fields. Advances in Neural Information Processing Systems
2020
Cited alongside, same era.
Peng, S., Niemeyer, M., Mescheder, L., Pollefeys, M., Geiger, A.: Convolutional Occupancy Networks. In: European Conference Computer Vision (ECCV). CVF (2020),
2020
Cited alongside, same era.
Teed, Z., Deng, J.: Raft: Recurrent all-pairs field transforms for optical flow. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16. pp. 402–419. Springer (2020)
2020
Cited alongside, same era.
Weder, S., Schonberger, J., Pollefeys, M., Oswald, M.R.: Routedfusion: Learning real-time depth map fusion. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4887–4897 (2020)
2020
Cited alongside, same era.
Zhang, H., Chen, G., Wang, Z., Wang, Z., Sun, L.: Dense 3d mapping for indoor environment based on feature-point slam method. In: 2020 the 4th International Conference on Innovation in Artificial Intelligence. pp. 42–46 (2020)
2020
Cited alongside, same era.
Keetha, N., Karhade, J., Jatavallabhula, K.M., Yang, G., Scherer, S., Ramanan, D., Luiten, J.: Splatam: Splat, track and map 3d gaussians for dense rgb-d slam. arXiv preprint (2023)
2023
Later among the works it cites.
Kerbl, B., Kopanas, G., Leimkühler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Transactions on Graphics
2023
Later among the works it cites.
Li, H., Gu, X., Yuan, W., Yang, L., Dong, Z., Tan, P.: Dense rgb slam with neural implicit maps. In: Proceedings of the International Conference on Learning Representations (2023),
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
Matsuki, H., Sucar, E., Laidow, T., Wada, K., Scona, R., Davison, A.J.: imode: Real-time incremental monocular dense mapping using neural field. In: 2023 IEEE International Conference on Robotics and Automation (ICRA). pp. 4171–4177. IEEE (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
Sandström, E., Li, Y., Van Gool, L., Oswald, M.R.: Point-slam: Dense neural point cloud-based slam. In: International Conference on Computer Vision (ICCV). IEEE/CVF (2023)
2023
Later among the works it cites.
Sandström, E., Ta, K., Gool, L.V., Oswald, M.R.: Uncle-SLAM: Uncertainty learning for dense neural SLAM. In: International Conference on Computer Vision Workshops (ICCVW) (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
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)
2023
Later among the works it cites.
2023
Later among the works it cites.
Yugay, V., Li, Y., Gevers, T., Oswald, M.R.: Gaussian-slam: Photo-realistic dense slam with gaussian splatting (2023)
2023
Later among the works it cites.
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)
2023
Later among the works it cites.
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)
2023
Later among the works it cites.
2023
Later among the works it cites.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
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)
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
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
Closest in time.