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With the increasing reliance of self-driving and similar robotic systems on robust 3D vision, the processing of LiDAR scans with deep convolutional neural networks has become a trend in academia and industry alike.
Acquiring 3d indoor environments with variability and repetition
Y. M. Kim, N. J. Mitra, D.-M. Yan, and L. Guibas · 2012
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Perceptual organization and recognition of indoor scenes from rgb-d images
S. Gupta, P. Arbelaez, and J. Malik · 2013
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A linear approach to matching cuboids in rgbd images
H. Jiang and J. Xiao · 2013
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Joint 3d scene reconstruction and class segmentation
C. Hane, C. Zach, A. Cohen, R. Angst, and M. Pollefeys · 2013
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Rapter: rebuilding man-made scenes with regular arrangements of planes
A. Monszpart, N. Mellado, G. J. Brostow, and N. J. Mitra · 2015
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Aligning 3d models to rgb-d images of cluttered scenes
S. Gupta, P. Arbeláez, R. Girshick, and J. Malik · 2015
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Joint 3d object and layout inference from a single rgb-d image
A. Geiger and C. Wang · 2015
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Database-assisted object retrieval for real-time 3d reconstruction
Y. Li, A. Dai, L. Guibas, and M. Nießner · 2015
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Structured prediction of unobserved voxels from a single depth image
M. Firman, O. Mac Aodha, S. Julier, and G. J. Brostow · 2016
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Heuristic 3d object shape completion based on symmetry and scene context
D. Schiebener, A. Schmidt, N. Vahrenkamp, and T. Asfour · 2016
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Deep sliding shapes for amodal 3d object detection in rgb-d images
S. Song and J. Xiao · 2016
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Large-scale semantic 3d reconstruction: an adaptive multi-resolution model for multi-class volumetric labeling
M. Blaha, C. Vogel, A. Richard, J. D. Wegner, T. Pock, and K. Schindler · 2016
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When 2.5 d is not enough: Simultaneous reconstruction, segmentation and recognition on dense slam
K. Tateno, F. Tombari, and N. Navab · 2016
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Nießner · 2017
Cited alongside, same era.
Semantic scene completion from a single depth image
S. Song, F. Yu, A. Zeng, A. X. Chang, M. Savva, and T. Funkhouser · 2017
Cited alongside, same era.
Octnetfusion: Learning depth fusion from data
G. Riegler, A. O. Ulusoy, H. Bischof, and A. Geiger · 2017
Cited alongside, same era.
Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
Cited alongside, same era.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Semantickitti: A dataset for semantic scene understanding of lidar sequences
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
C. Choy, J. Gwak, and S. Savarese · 2019
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Squeezesegv2: Improved model structure and unsupervised domain adaptation for road-object segmentation from a lidar point cloud
B. Wu, X. Zhou, S. Zhao, X. Yue, and K. Keutzer · 2019
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Deeptemporalseg: Temporally consistent semantic segmentation of 3d lidar scans
A. Dewan and W. Burgard · 2019
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Salsanet: Fast road and vehicle segmentation in lidar point clouds for autonomous driving
E. E. Aksoy, S. Baci, and S. Cavdar · 2019
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C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
Cited alongside, same era.
Learning affinity via spatial propagation networks
S. Liu, S. De Mello, J. Gu, G. Zhong, M.-H. Yang, and J. Kautz · 2017
Cited alongside, same era.
Pointseg: Real-time semantic segmentation based on 3d lidar point cloud
Y. Wang, T. Shi, P. Yun, L. Tai, and M. Liu · 2018
Cited alongside, same era.
Hdnet: Exploiting hd maps for 3d object detection
B. Yang, M. Liang, and R. Urtasun · 2018
Cited alongside, same era.
See and think: Disentangling semantic scene completion
S. Liu, Y. Hu, Y. Zeng, Q. Tang, B. Jin, Y. Han, and X. Li · 2018
Cited alongside, same era.
3dmv: Joint 3d-multi-view prediction for 3d semantic scene segmentation
A. Dai and M. Nießner · 2018
Cited alongside, same era.
In defense of classical image processing: Fast depth completion on the cpu
J. Ku, A. Harakeh, and S. L. Waslander · 2018
Cited alongside, same era.
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Two stream 3d semantic scene completion
M. Garbade, Y.-T. Chen, J. Sawatzky, and J. Gall · 2019
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Depth based semantic scene completion with position importance aware loss
J. Li, Y. Liu, X. Yuan, C. Zhao, R. Siegwart, I. Reid, and C. Cadena · 2019
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Rgbd based dimensional decomposition residual network for 3d semantic scene completion
J. Li, Y. Liu, D. Gong, Q. Shi, X. Yuan, C. Zhao, and I. Reid · 2019
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Randla-net: Efficient semantic segmentation of large-scale point clouds
Q. Hu, B. Yang, L. Xie, S. Rosa, Y. Guo, Z. Wang, N. Trigoni, and A. Markham · 2020
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Salsanext: Fast semantic segmentation of lidar point clouds for autonomous driving
T. Cortinhal, G. Tzelepis, and E. E. Aksoy · 2020
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nuscenes: A multimodal dataset for autonomous driving
H. Caesar, V. Bankiti, A. H. Lang, S. Vora, V. E. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, and O. Beijbom · 2020
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Anisotropic convolutional networks for 3d semantic scene completion
J. Li, K. Han, P. Wang, Y. Liu, and X. Yuan · 2020
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