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We introduce a new task, novel view synthesis for LiDAR sensors.
Image quality assessment: from error visibility to structural similarity
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Poisson surface reconstruction
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Adam: A method for stochastic optimization
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Tanks and temples: Benchmarking large-scale scene reconstruction
A. Knapitsch, J. Park, Q.-Y. Zhou, and V. Koltun · 2017
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Carla: An open urban driving simulator
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
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Colored point cloud registration revisited
J. Park, Q.-Y. Zhou, and V. Koltun · 2017
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A lidar point cloud generator: from a virtual world to autonomous driving
X. Yue, B. Wu, S. A. Seshia, K. Keutzer, and A. L. Sangiovanni-Vincentelli · 2018
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Squeezeseg: Convolutional neural nets with recurrent crf for real-time road-object segmentation from 3d lidar point cloud
B. Wu, A. Wan, X. Yue, and K. Keutzer · 2018
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Open3d: A modern library for 3d data processing
Q.-Y. Zhou, J. Park, and V. Koltun · 2018
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Digging into self-supervised monocular depth estimation
C. Godard, O. Mac Aodha, M. Firman, and G. J. Brostow · 2019
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Lidarsim: Realistic lidar simulation by leveraging the real world
S. Manivasagam, S. Wang, K. Wong, W. Zeng, M. Sazanovich, S. Tan, B. Yang, W.-C. Ma, and R. Urtasun · 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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Scalability in perception for autonomous driving: Waymo open dataset
P. Sun, H. Kretzschmar, X. Dotiwalla, A. Chouard, V. Patnaik, P. Tsui, J. Guo, Y. Zhou, Y. Chai, B. Caine, et al · 2020
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Neural sparse voxel fields
L. Liu, J. Gu, K. Zaw Lin, T.-S. Chua, and C. Theobalt · 2020
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Nerf-pytorch
L. Yen-Chen · 2020
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Domain transfer for semantic segmentation of lidar data using deep neural networks
F. Langer, A. Milioto, A. Haag, J. Behley, and C. Stachniss · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng · 2021
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Neural scene graphs for dynamic scenes
J. Ost, F. Mannan, N. Thuerey, J. Knodt, and F. Heide · 2021
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Plenoxels: Radiance fields without neural networks
A. Yu, S. Fridovich-Keil, M. Tancik, Q. Chen, B. Recht, and A. Kanazawa · 2021
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pixelnerf: Neural radiance fields from one or few images
A. Yu, V. Ye, M. Tancik, and A. Kanazawa · 2021
Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
Y. Liao, J. Xie, and A. Geiger · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
T. Müller, A. Evans, C. Schied, and A. Keller · 2022
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Tensorf: Tensorial radiance fields
A. Chen, Z. Xu, A. Geiger, J. Yu, and H. Su · 2022
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Infonerf: Ray entropy minimization for few-shot neural volume rendering
M. Kim, S. Seo, and B. Han · 2022
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Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
M. Niemeyer, J. T. Barron, B. Mildenhall, M. S. Sajjadi, A. Geiger, and N. Radwan · 2022
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Depth-supervised nerf: Fewer views and faster training for free
K. Deng, A. Liu, J.-Y. Zhu, and D. Ramanan · 2022
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Donerf: Towards real-time rendering of compact neural radiance fields using depth oracle networks
T. Neff, P. Stadlbauer, M. Parger, A. Kurz, J. H. Mueller, C. R. A. Chaitanya, A. Kaplanyan, and M. Steinberger · 2021
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Kitti-carla: a kitti-like dataset generated by carla simulator
J.-E. Deschaud · 2021
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D-nerf: Neural radiance fields for dynamic scenes
A. Pumarola, E. Corona, G. Pons-Moll, and F. Moreno-Noguer · 2021
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Grf: Learning a general radiance field for 3d representation and rendering
A. Trevithick and B. Yang · 2021
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
J. T. Barron, B. Mildenhall, M. Tancik, P. Hedman, R. Martin-Brualla, and P. P. Srinivasan · 2021
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Urban radiance fields
K. Rematas, A. Liu, P. P. Srinivasan, J. T. Barron, A. Tagliasacchi, T. Funkhouser, and V. Ferrari · 2022
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Dense depth priors for neural radiance fields from sparse input views
B. Roessle, J. T. Barron, B. Mildenhall, P. P. Srinivasan, and M. Nießner · 2022
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Transfer learning from synthetic to real lidar point cloud for semantic segmentation
A. Xiao, J. Huang, D. Guan, F. Zhan, and S. Lu · 2022
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Learning to simulate realistic lidars
B. Guillard, S. Vemprala, J. K. Gupta, O. Miksik, V. Vineet, P. Fua, and A. Kapoor · 2022
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Panoptic nerf: 3d-to-2d label transfer for panoptic urban scene segmentation
X. Fu, S. Zhang, T. Chen, Y. Lu, L. Zhu, X. Zhou, A. Geiger, and Y. Liao · 2022
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D-tensorf: Tensorial radiance fields for dynamic scenes
H. Jang and D. Kim · 2022
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Torch-ngp: a pytorch implementation of instant-ngp, 2022
J. Tang · 2022
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Benchmarking the robustness of lidar-camera fusion for 3d object detection
K. Yu, T. Tao, H. Xie, Z. Lin, Z. Wu, Z. Xia, T. Liang, H. Sun, J. Deng, D. Hao, et al · 2022
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S-nerf: Neural radiance fields for street views
Z. Xie, J. Zhang, W. Li, F. Zhang, and L. Zhang · 2023
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