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We study how state-of-the-art neural networks for 3D object detection using a single-stage pipeline can be made safety aware.
Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints
P. Cousot and R. Cousot · 1977
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Vision meets robotics: The KITTI dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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Vehicle detection from 3d lidar using fully convolutional network
B. Li, T. Zhang, and T. Xia · 2016
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Multi-view 3d object detection network for autonomous driving
X. Chen, H. Ma, J. Wan, B. Li, and T. Xia · 2017
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Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks
M. Engelcke, D. Rao, D. Z. Wang, C. H. Tong, and I. Posner · 2017
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Structuring validation targets of a machine learning function applied to automated driving
L. Gauerhof, P. Munk, and S. Burton · 2018
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A survey of safety and trustworthiness of deep neural networks
X. Huang, D. Kroening, W. Ruan, J. Sharp, Y. Sun, E. Thamo, M. Wu, and X. Yi · 2018
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Certified defenses against adversarial examples
A. Raghunathan, J. Steinhardt, and P. Liang · 2018
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Certifying some distributional robustness with principled adversarial training
A. Sinha, H. Namkoong, and J. C. Duchi · 2018
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Lipschitz-margin training: Scalable certification of perturbation invariance for deep neural networks
Y. Tsuzuku, I. Sato, and M. Sugiyama · 2018
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Mixtrain: Scalable training of formally robust neural networks
S. Wang, Y. Chen, A. Abdou, and S. Jana · 2018
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Provable defenses against adversarial examples via the convex outer adversarial polytope
E. Wong and Z. Kolter · 2018
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Scaling provable adversarial defenses
PIXOR: Real-time 3D object detection from point clouds
B. Yang, W. Luo, and R. Urtasun · 2018
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Confidence arguments for evidence of performance in machine learning for highly automated driving functions
S. Burton, L. Gauerhof, B. B. Sethy, I. Habli, and R. Hawkins · 2019
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Credible autonomy safety argumentation
P. Koopman, A. Kane, and J. Black · 2019
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Tackling uncertainty in safety assurance for machine learning: Continuous argument engineering with attributed tests
Y. Matsuno, F. Ishikawa, and S. Tokumoto · 2019
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Provably robust deep learning via adversarially trained smoothed classifiers
H. Salman, G. Yang, J. Li, P. Zhang, H. Zhang, I. Razenshteyn, and S. Bubeck · 2019
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E. Wong, F. Schmidt, J. H. Metzen, and J. Z. Kolter · 2018
Cited alongside, same era.
PointrRCNN: 3d object proposal generation and detection from point cloud
S. Shi, X. Wang, and H. Li · 2019
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