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We present a dense simultaneous localization and mapping (SLAM) method that uses 3D Gaussians as a scene representation.
Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. ACM siggraph computer graphics 21
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.
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 13
2004
Earlier work this paper cites.
Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: Monoslam: Real-time single camera slam. IEEE transactions on pattern analysis and machine intelligence 29
2007
Earlier work this paper cites.
Klein, G., Murray, D.: Parallel tracking and mapping for small ar workspaces. In: 2007 6th IEEE and ACM international symposium on mixed and augmented reality. pp. 225–234. IEEE (2007)
2007
Earlier work this paper cites.
Stühmer, J., Gumhold, S., Cremers, D.: Real-time dense geometry from a handheld camera. In: Joint Pattern Recognition Symposium. pp. 11–20. Springer (2010)
2010
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.
Newcombe, R.A., Lovegrove, S.J., Davison, A.J.: Dtam: Dense tracking and mapping in real-time. In: International Conference on Computer Vision (ICCV) (2011)
2011
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, http://ieeexplore.ieee.org/document/6385773/
2012
Earlier work this paper cites.
Whelan, T., McDonald, J., Kaess, M., Fallon, M., Johannsson, H., Leonard, J.J.: Kintinuous: Spatially extended kinectfusion. In: Proceedings of RSS ’12 Workshop on RGB-D: Advanced Reasoning with Depth Cameras (2012)
2012
Earlier work this paper cites.
Chen, J., Bautembach, D., Izadi, S.: Scalable real-time volumetric surface reconstruction. ACM Transactions on Graphics (ToG) 32
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.
Nießner, M., Zollhöfer, M., Izadi, S., Stamminger, M.: Real-time 3d reconstruction at scale using voxel hashing. ACM Transactions on Graphics (TOG) 32
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.
Zhou, Q.Y., Koltun, V.: Dense scene reconstruction with points of interest. ACM Transactions on Graphics (TOG) 32
2013
Earlier work this paper cites.
Zhou, Q.Y., Miller, S., Koltun, V.: Elastic fragments for dense scene reconstruction. Proceedings of the IEEE International Conference on Computer Vision pp. 2726–2733 (2013)
2013
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 25
2014
Earlier work this paper cites.
Choi, S., Zhou, Q.Y., Koltun, V.: Robust reconstruction of indoor scenes. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 5556–5565 (2015)
2015
Earlier work this paper cites.
Fuentes-Pacheco, J., Ruiz-Ascencio, J., Rendón-Mancha, J.M.: Visual simultaneous localization and mapping: a survey. Artificial intelligence review 43
2015
Earlier work this paper cites.
Kähler, O., Prisacariu, V., Valentin, J., Murray, D.: Hierarchical voxel block hashing for efficient integration of depth images. IEEE Robotics and Automation Letters 1
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. 21
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.
Bylow, E., Olsson, C., Kahl, F.: Robust online 3d reconstruction combining a depth sensor and sparse feature points. In: 2016 23rd International Conference on Pattern Recognition (ICPR). pp. 3709–3714 (2016)
2016
Earlier work this paper cites.
Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nießner, M.: ScanNet: Richly-annotated 3D reconstructions of indoor scenes. In: Conference on Computer Vision and Pattern Recognition (CVPR). IEEE/CVF (2017). https://doi.org/10.1109/CVPR.2017.261
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) 36
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.
Mur-Artal, R., Tardos, J.D.: ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics 33
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, https://doi.org/10.1109/IROS.2017.8202315
2017
Earlier work this paper cites.
Park, J., Zhou, Q.Y., Koltun, V.: Colored point cloud registration revisited. In: Proceedings of the IEEE international conference on computer vision. pp. 143–152 (2017)
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) 37
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.
Zollhöfer, M., Stotko, P., Görlitz, A., Theobalt, C., Nießner, M., Klein, R., Kolb, A.: State of the art on 3d reconstruction with rgb-d cameras. In: Computer graphics forum. vol. 37, pp. 625–652. Wiley Online Library (2018)
2018
Cited alongside, same era.
Li, K., Tang, Y., Prisacariu, V.A., Torr, P.H.: Bnv-fusion: Dense 3d reconstruction using bi-level neural volume fusion. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6166–6175 (2022)
2022
Later among the works it cites.
Mahdi Johari, M., Carta, C., Fleuret, F.: Eslam: Efficient dense slam system based on hybrid representation of signed distance fields. arXiv e-prints pp. arXiv–2211 (2022)
2022
Later among the works it cites.
Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41
2022
Later among the works it cites.
2022
Later among the works it cites.
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Johnson, J., Douze, M., Jégou, H.: Billion-scale similarity search with GPUs. IEEE Transactions on Big Data 7
2019
Cited alongside, same era.
Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: Learning 3d reconstruction in function space. In: IEEE/CVF conference on computer vision and pattern recognition. pp. 4460–4470 (2019)
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., Lin, K.Z., Chua, T.S., Theobalt, C.: Neural sparse voxel fields. In: Advances in Neural Information Processing Systems. vol. 33, pp. 15651–15663 (2020)
2020
Cited alongside, same era.
Murez, Z., van As, T., Bartolozzi, J., Sinha, A., Badrinarayanan, V., Rabinovich, A.: Atlas: End-to-end 3d scene reconstruction from posed images. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part VII 16. pp. 414–431. Springer (2020)
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), https://www.microsoft.com/en-us/research/publication/convolutional-occupancy-networks/
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.
2022
Later among the works it cites.
Sayed, M., Gibson, J., Watson, J., Prisacariu, V., Firman, M., Godard, C.: Simplerecon: 3d reconstruction without 3d convolutions. In: European Conference on Computer Vision. pp. 1–19. Springer (2022)
2022
Later among the works it cites.
Wang, J., Wang, P., Long, X., Theobalt, C., Komura, T., Liu, L., Wang, W.: Neuris: Neural reconstruction of indoor scenes using normal priors. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXII. pp. 139–155. Springer (2022)
2022
Later among the works it cites.
Xu, Q., Xu, Z., Philip, J., Bi, S., Shu, Z., Sunkavalli, K., Neumann, U.: Point-nerf: Point-based neural radiance fields. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5438–5448 (2022)
2022
Later among the works it cites.
Yang, X., Li, H., Zhai, H., Ming, Y., Liu, Y., Zhang, G.: Vox-fusion: Dense tracking and mapping with voxel-based neural implicit representation. In: IEEE International Symposium on Mixed and Augmented Reality (ISMAR). pp. 499–507. IEEE (2022)
2022
Later among the works it cites.
Yang, X., Ming, Y., Cui, Z., Calway, A.: Fd-slam: 3-d reconstruction using features and dense matching. In: 2022 International Conference on Robotics and Automation (ICRA). pp. 8040–8046. IEEE (2022)
2022
Later among the works it cites.
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)
2022
Later among the works it cites.
Gao, Y., Cao, Y.P., Shan, Y.: Surfelnerf: Neural surfel radiance fields for online photorealistic reconstruction of indoor scenes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 108–118 (2023)
2023
Closest in time.
Huang, H., Li, L., Cheng, H., Yeung, S.K.: Photo-slam: Real-time simultaneous localization and photorealistic mapping for monocular, stereo, and rgb-d cameras (2023)
2023
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Keetha, N., Karhade, J., Jatavallabhula, K.M., Yang, G., Scherer, S., Ramanan, D., Luiten, J.: Splatam: Splat, track & map 3d gaussians for dense rgb-d slam. arXiv preprint (2023)
2023
Closest in time.
Kerbl, B., Kopanas, G., Leimkühler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Transactions on Graphics 42
2023
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2023
Closest in time.
Liu, D., Chen, C., Xu, C., Qiu, R.C., Chu, L.: Self-supervised point cloud registration with deep versatile descriptors for intelligent driving. IEEE Transactions on Intelligent Transportation Systems (2023)
2023
Closest in time.
Luiten, J., Kopanas, G., Leibe, B., Ramanan, D.: Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis (2023)
2023
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Matsuki, H., Murai, R., Kelly, P.H.J., Davison, A.J.: Gaussian splatting slam (2023)
2023
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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
Closest in time.
Sandström, E., Ta, K., Van Gool, L., Oswald, M.R.: Uncle-slam: Uncertainty learning for dense neural slam. In: International Conference on Computer Vision Workshops (ICCVW). IEEE/CVF (2023)
2023
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2023
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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. pp. 13293–13302 (2023)
2023
Closest in time.
Wu, G., Yi, T., Fang, J., Xie, L., Zhang, X., Wei, W., Liu, W., Tian, Q., Wang, X.: 4d gaussian splatting for real-time dynamic scene rendering (2023)
2023
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Yang, Z., Yang, H., Pan, Z., Zhu, X., Zhang, L.: Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting (2023)
2023
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Yang, Z., Gao, X., Zhou, W., Jiao, S., Zhang, Y., Jin, X.: Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction (2023)
2023
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Yeshwanth, C., Liu, Y.C., Nießner, M., Dai, A.: Scannet++: A high-fidelity dataset of 3d indoor scenes. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 12–22 (2023)
2023
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2023
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Yan, C., Qu, D., Wang, D., Xu, D., Wang, Z., Zhao, B., Li, X.: Gs-slam: Dense visual slam with 3d gaussian splatting (2024)
2024
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