HGS-Mapping: Online Dense Mapping Using Hybrid Gaussian Representation in Urban Scenes

Curless, B., Levoy, M.: A volumetric method for building complex models from range images. In: Proceedings of the 23rd annual conference on Computer graphics and interactive techniques. pp. 303–312 (1996)

1996

Earlier work this paper cites.

Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. In: Seminal graphics: pioneering efforts that shaped the field, pp. 347–353 (1998)

1998

Earlier work this paper cites.

Zwicker, M., Pfister, H., Van Baar, J., Gross, M.: Ewa volume splatting. In: Proceedings Visualization, 2001. VIS’01. pp. 29–538. IEEE (2001)

2001

Earlier work this paper cites.

Geiger, A., Lenz, P., Stiller, C., Urtasun, R.: Vision meets robotics: The kitti dataset. The International Journal of Robotics Research 32

2013

Earlier work this paper cites.

Schönberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)

2016

Earlier work this paper cites.

Whelan, T., Salas-Moreno, R.F., Glocker, B., Davison, A.J., Leutenegger, S.: Elasticfusion: Real-time dense slam and light source estimation. The International Journal of Robotics Research 35

2016

Earlier work this paper cites.

Chen, L.C., Papandreou, G., Schroff, F., Adam, H.: Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017)

Original

2017

Earlier work this paper cites.

Mur-Artal, R., Tardós, 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.

Qin, T., Li, P., Shen, S.: Vins-mono: A robust and versatile monocular visual-inertial state estimator. IEEE Transactions on Robotics 34

2018

Earlier work this paper cites.

Zhou, Q.Y., Park, J., Koltun, V.: Open3d: A modern library for 3d data processing. arXiv preprint arXiv:1801.09847 (2018)

Original

2018

Earlier work this paper cites.

Labbé, M., Michaud, F.: Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation. Journal of field robotics 36

2019

Earlier work this paper cites.

Cabon, Y., Murray, N., Humenberger, M.: Virtual kitti 2 (2020)

2020

Earlier work this paper cites.

Caesar, H., Bankiti, V., Lang, A.H., Vora, S., Liong, V.E., Xu, Q., Krishnan, A., Pan, Y., Baldan, G., Beijbom, O.: nuscenes: A multimodal dataset for autonomous driving. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 11621–11631 (2020)

2020

Earlier work this paper cites.

Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: European Conference on Computer Vision. pp. 405–421. Springer (2020)

2020

Earlier work this paper cites.

Sun, P., Kretzschmar, H., Dotiwalla, X., Chouard, A., Patnaik, V., Tsui, P., Guo, J., Zhou, Y., Chai, Y., Caine, B., et al.: Scalability in perception for autonomous driving: Waymo open dataset. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 2446–2454 (2020)

2020

Earlier work this paper cites.

Zhang, K., Riegler, G., Snavely, N., Koltun, V.: Nerf++: Analyzing and improving neural radiance fields. arXiv preprint arXiv:2010.07492 (2020)

Original

2020

Earlier work this paper cites.

Ost, J., Mannan, F., Thuerey, N., Knodt, J., Heide, F.: Neural scene graphs for dynamic scenes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2856–2865 (2021)

2021

Cited alongside, same era.

Sucar, E., Liu, S., Ortiz, J., Davison, A.J.: imap: Implicit mapping and positioning in real-time. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 6229–6238 (2021)

2021

Cited alongside, same era.

Barron, J.T., Mildenhall, B., Verbin, D., Srinivasan, P.P., Hedman, P.: Mip-nerf 360: Unbounded anti-aliased neural radiance fields. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5470–5479 (2022)

2022

Cited alongside, same era.

Hu, J., Bao, C., Ozay, M., Fan, C., Gao, Q., Liu, H., Lam, T.L.: Deep depth completion from extremely sparse data: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)

2022

Cited alongside, same era.

Luiten, J., Kopanas, G., Leibe, B., Ramanan, D.: Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis. arXiv preprint arXiv:2308.09713 (2023)

Original

2023

Later among the works it cites.

Matsuki, H., Murai, R., Kelly, P.H., Davison, A.J.: Gaussian splatting slam. arXiv preprint arXiv:2312.06741 (2023)

Original

2023

Later among the works it cites.

Turki, H., Zhang, J.Y., Ferroni, F., Ramanan, D.: Suds: Scalable urban dynamic scenes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12375–12385 (2023)

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. pp. 13293–13302 (2023)

2023

Later among the works it cites.