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We propose a novel end-to-end RGB-D SLAM, iDF-SLAM, which adopts a feature-based deep neural tracker as the front-end and a NeRF-style neural implicit mapper as the back-end.
R. A. Newcombe, S. Izadi, O. Hilliges, D. Molyneaux, D. Kim, A. J. Davison, P. Kohi, J. Shotton, S. Hodges and A. Fitzgibbon. “KinectFusion: Real-time Dense Surface Mapping and Tracking,” in IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
2011
Earlier work this paper cites.
C. Kerl, J. Sturm and D. Cremers. “Dense Visual SLAM for RGB-D Cameras,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2013
Earlier work this paper cites.
R. Mur-Artal, J. Montiel and J. Tardos. “ORB-SLAM : A Versatile and Accurate Monocular,” in IEEE Transactions on Robotics (T-RO)
2015
Earlier work this paper cites.
T. Whelan, S. Leutenegger, R. Salas Moreno, B. Glocker, and A. J. Davison. ElasticFusion: Dense SLAM Without A Pose Graph. In Robotics: Science and Systems (RSS), 2015
2015
Earlier work this paper cites.
D. P. Kingma and J. Ba. “ADAM: A method for stochastic optimization,” In International Conference on Learning Representations (ICLR)
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren and J. Sun. “Deep Residual Learning for Image Recognition Kaiming,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2016
Earlier work this paper cites.
A. Dai, M. Nießner, M. Zollhöofer, S. Izadi and C. Theobalt. “Bundlefusion: Real-time Globally Consistent 3D Reconstruction Using on-the-fly Surface Reintegration,” in ACM Transactions on Graphics (ToG)
2017
Earlier work this paper cites.
N. Sünderhauf, T. T. Pham, Y. Latif, M. Milford and I. Reid. “Meaningful Maps with Object-oriented Semantic Mapping,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2017
Earlier work this paper cites.
, J. McCormac, A. Handa, A. Davison and S. Leutenegger. “SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks,” in IEEE International Conference on Robotics and Automation (ICRA)
2017
Earlier work this paper cites.
A. Dai, A. Chang, M. Savva, M. Halber, T. Funkhouser and M. Nießner. “ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2017
Earlier work this paper cites.
M. Bloesch, J. Czarnowski, R. Clark, S. Leutenegger and A. J. Davison. “CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2018
Earlier work this paper cites.
S. Zhi, M. Bloesch, S. Leutenegger and A. J. Davison. “SceneCode: Monocular Dense Semantic Reconstruction Using Learned Encoded Scene Representations,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2019
Earlier work this paper cites.
2019
Cited alongside, same era.
Z. Liao, W. Wang, X. Qi, and X. Zhang. “RGB-D Object Slam Using Quadrics for Indoor Environments,” in Sensors
2020
Cited alongside, same era.
J. Czarnowski, T. Laidlow, R. Clark and A. J. Davison. “DeepFactors: Real-Time Probabilistic Dense Monocular SLAM,” in IEEE Robotics and Automation Letters (R-AL
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,” in European Conference on Computer Vision (ECCV)
2020
Cited alongside, same era.
L. Liu, J. Gu, K. Z. Lin, T. Chua and C. Theobalt. “Neural Sparse Voxel Fields,” in Advances in Neural Information Processing Systems (NeurIPS)
S. Lionar, L. Schmid, C. Cadena, R. Siegwart and A. Cramariuc. ”NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping,” in International Conference on 3D Vision (3DV)
2021
Later among the works it cites.
L. Yen-Chen, P. Florence, J. T. Barron, A. Rodriguez, P. Isola and T. Lin. “INeRF: Inverting Neural Radiance Fields for Pose Estimation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2021
Later among the works it cites.
2021
Later among the works it cites.
C. Lin, W. Ma, A. Torralba and S. Lucey. “BARF: Bundle-Adjusting Neural Radiance Fields,” in IEEE/CVF International Conference on Computer Vision (ICCV)
2021
Later among the works it cites.
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2020
Cited alongside, same era.
C. Choy, W. Dong and V. Kultun. “Deep global registration,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2020
Cited alongside, same era.
A. Sharma, W. Dong and M. Kaess. “Compositional and Scalable Object SLAM,” in IEEE International Conference on Robotics and Automation (ICRA)
2021
Cited alongside, same era.
Y. Ming, X. Yang and Andrew Calway. “Object-Augmented RGB-D SLAM for Wide-Disparity Relocalisation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2021
Cited alongside, same era.
H. Matsuki, R. Scona, J. Czarnowski and A. J. Davison. “CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations,” in IEEE Robotics and Automation Letters (R-AL)
2021
Cited alongside, same era.
E. Sucar, S. Liu, J. Ortiz and A. J. Davison. “iMAP: Implicit Mapping and Positioning in Real-Time,” in IEEE/CVF International Conference on Computer Vision (ICCV)
2021
Cited alongside, same era.
M. Oechsle, S. Peng and A. Geiger. “UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction,” in IEEE/CVF International Conference on Computer Vision (ICCV)
2021
Cited alongside, same era.
P. Wang, L. Liu, Y. Liu, C. Theobal, T. Komura and W. Wang. “NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction,” in Advances in Neural Information Processing Systems (NeurIPS)
2021
Cited alongside, same era.
M. E. Banani, L. Gao and J. Johnson. “UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2021
Later among the works it cites.
W. Dai, Y. Zhang, P. Li, Z. Fang and S. Scherer. “RGB-D SLAM in Dynamic Environments Using Point Correlations,” in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
2022
Closest in time.
X. Yang, Y. Ming, Z. Cui and A. Calway. “FD-SLAM: 3-D Reconstruction Using Features and Dense Matching,” in IEEE International Conference on Robotics and Automation (ICRA)
2022
Closest in time.
2022
Closest in time.
2022
Closest in time.
Y. Ming, X. Yang, G. Zhang and A. Calway. “CGiS-Net: Aggregating Colour, Geometry and Implicit Semantic Features for Indoor Place Recognition,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2022
Closest in time.
D. Azinović, R. Martin-Brualla, D. B. Goldman, Matthias Nießner and J. Thies. “Neural RGB-D Surface Reconstruction,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2022
Closest in time.