Fetching the paper…
Reading the bibliography…
3D Point cloud is becoming a critical data representation in many real-world applications like autonomous driving, robotics, and medical imaging.
An efficient image similarity measure based on approximations of kl-divergence between two gaussian mixtures
J. Goldberger, S. Gordon, H. Greenspan, et al · 2003
Earlier work this paper cites.
Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2014
Earlier work this paper cites.
Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
Earlier work this paper cites.
Voting for voting in online point cloud object detection
D. Z. Wang and I. Posner · 2015
Earlier work this paper cites.
3d shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Distillation as a defense to adversarial perturbations against deep neural networks
N. Papernot, P. McDaniel, X. Wu, S. Jha, and A. Swami · 2016
Earlier work this paper cites.
Deep Sliding Shapes for amodal 3D object detection in RGB-D images
S. Song and J. Xiao · 2016
Earlier work this paper cites.
Towards evaluating the robustness of neural networks
N. Carlini and D. Wagner · 2017
Earlier work this paper cites.
Submanifold sparse convolutional networks
B. Graham and L. van der Maaten · 2017
Earlier work this paper cites.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2017
Earlier work this paper cites.
Magnet: a two-pronged defense against adversarial examples
D. Meng and H. Chen · 2017
Earlier work this paper cites.
Extending defensive distillation
N. Papernot and P. McDaniel · 2017
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
Earlier work this paper cites.
Octnet: Learning deep 3d representations at high resolutions
G. Riegler, A. O. Ulusoy, and A. Geiger · 2017
Earlier work this paper cites.
Segcloud: Semantic segmentation of 3d point clouds
L. P. Tchapmi, C. B. Choy, I. Armeni, J. Gwak, and S. Savarese · 2017
Earlier work this paper cites.
O-cnn: Octree-based convolutional neural networks for 3d shape analysis
P.-S. Wang, Y. Liu, Y.-X. Guo, C.-Y. Sun, and X. Tong · 2017
Earlier work this paper cites.
Adversarial examples for semantic segmentation and object detection
C. Xie, J. Wang, Z. Zhang, Y. Zhou, L. Xie, and A. Yuille · 2017
Earlier work this paper cites.
Feature squeezing: Detecting adversarial examples in deep neural networks
W. Xu, D. Evans, and Y. Qi · 2017
Earlier work this paper cites.
Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
A. Athalye, N. Carlini, and D. Wagner · 2018
Earlier work this paper cites.
Synthesizing robust adversarial examples
A. Athalye, L. Engstrom, A. Ilyas, and K. Kwok · 2018
Earlier work this paper cites.
Thwarting adversarial examples: An l _ 0 l\_0 -robustsparse fourier transform
M. Bafna, J. Murtagh, and N. Vyas · 2018
Earlier work this paper cites.
Stochastic activation pruning for robust adversarial defense
G. S. Dhillon, K. Azizzadenesheli, Z. C. Lipton, J. Bernstein, J. Kossaifi, A. Khanna, and A. Anandkumar · 2018
Earlier work this paper cites.
Robust physical-world attacks on deep learning visual classification
K. Eykholt, I. Evtimov, E. Fernandes, B. Li, A. Rahmati, C. Xiao, A. Prakash, T. Kohno, and D. Song · 2018
Earlier work this paper cites.
Pointcnn: Convolution on x-transformed points
Y. Li, R. Bu, M. Sun, W. Wu, X. Di, and B. Chen · 2018
Earlier work this paper cites.
Adversarial risk and the dangers of evaluating against weak attacks
J. Uesato, B. O’donoghue, P. Kohli, and A. Oord · 2018
Earlier work this paper cites.
Characterizing adversarial examples based on spatial consistency information for semantic segmentation
C. Xiao, R. Deng, B. Li, F. Yu, M. Liu, and D. Song · 2018
Earlier work this paper cites.
Generating adversarial examples with adversarial networks
C. Xiao, B. Li, J.-Y. Zhu, W. He, M. Liu, and D. Song · 2018
Earlier work this paper cites.
Spatially transformed adversarial examples
C. Xiao, J.-Y. Zhu, B. Li, W. He, M. Liu, and D. Song · 2018
Cited alongside, same era.
Adversarial sensor attack on lidar-based perception in autonomous driving
Y. Cao, C. Xiao, B. Cyr, Y. Zhou, W. Park, S. Rampazzi, Q. A. Chen, K. Fu, and Z. M. Mao · 2019
Cited alongside, same era.
On evaluating adversarial robustness
N. Carlini, A. Athalye, N. Papernot, W. Brendel, J. Rauber, D. Tsipras, I. Goodfellow, A. Madry, and A. Kurakin · 2019
Cited alongside, same era.
4d spatio-temporal convnets: Minkowski convolutional neural networks
C. Choy, J. Gwak, and S. Savarese · 2019
Cited alongside, same era.
Certified adversarial robustness via randomized smoothing
J. Cohen, E. Rosenfeld, and Z. Kolter · 2019
Cited alongside, same era.
Universal physical camouflage attacks on object detectors
L. Huang, C. Gao, Y. Zhou, C. Xie, A. L. Yuille, C. Zou, and N. Liu · 2020
Later among the works it cites.
Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
S. Shi, C. Guo, L. Jiang, Z. Wang, J. Shi, X. Wang, and H. Li · 2020
Later among the works it cites.
Towards robust lidar-based perception in autonomous driving: General black-box adversarial sensor attack and countermeasures
J. Sun, Y. Cao, Q. A. Chen, and Z. M. Mao · 2020
Later among the works it cites.
On the adversarial robustness of 3d point cloud classification, 2020
J. Sun, K. Koenig, Y. Cao, Q. A. Chen, and Z. M. Mao · 2020
Later among the works it cites.
On adaptive attacks to adversarial example defenses
F. Tramer, N. Carlini, W. Brendel, and A. Madry · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Universal physical camouflage attacks on object detectors, 2019
L. Huang, C. Gao, Y. Zhou, C. Xie, A. Yuille, C. Zou, and N. Liu · 2019
Cited alongside, same era.
Nattack: Learning the distributions of adversarial examples for an improved black-box attack on deep neural networks
Y. Li, L. Li, L. Wang, T. Zhang, and B. Gong · 2019
Cited alongside, same era.
Extending adversarial attacks and defenses to deep 3d point cloud classifiers
D. Liu, R. Yu, and H. Su · 2019
Cited alongside, same era.
Relation-shape convolutional neural network for point cloud analysis
Y. Liu, B. Fan, S. Xiang, and C. Pan · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, et al · 2019
Cited alongside, same era.
Adversarial training for free!
A. Shafahi, M. Najibi, A. Ghiasi, Z. Xu, J. Dickerson, C. Studer, L. S. Davis, G. Taylor, and T. Goldstein · 2019
Cited alongside, same era.
Pointrcnn: 3d object proposal generation and detection from point cloud
S. Shi, X. Wang, and H. Li · 2019
Cited alongside, same era.
Robust adversarial objects against deep learning models
T. Tsai, K. Yang, T.-Y. Ho, and Y. Jin · 2020
Later among the works it cites.
Fast is better than free: Revisiting adversarial training
E. Wong, L. Rice, and J. Z. Kolter · 2020
Later among the works it cites.
If-defense: 3d adversarial point cloud defense via implicit function based restoration
Z. Wu, Y. Duan, H. Wang, Q. Fan, and L. J. Guibas · 2020
Later among the works it cites.
C. Xie, M. Tan, B. Gong, A. Yuille, and Q. V. Le · 2020
Later among the works it cites.
Intriguing properties of adversarial training at scale
C. Xie and A. Yuille · 2020
Later among the works it cites.
Patchattack: A black-box texture-based attack with reinforcement learning
C. Yang, A. Kortylewski, C. Xie, Y. Cao, and A. Yuille · 2020
Later among the works it cites.
Robust deep reinforcement learning against adversarial perturbations on observations
H. Zhang, H. Chen, C. Xiao, B. Li, D. S. Boning, and C.-J. Hsieh · 2020
Later among the works it cites.
Lg-gan: Label guided adversarial network for flexible targeted attack of point cloud based deep networks
H. Zhou, D. Chen, J. Liao, K. Chen, X. Dong, K. Liu, W. Zhang, G. Hua, and N. Yu · 2020
Later among the works it cites.
https://paperswithcode.com/sota/3d-point-cloud-classification-on-modelnet40 , 2021
3D Point Cloud Classification Benchmark on ModelNet40 · 2021
Later among the works it cites.
Diffusion models beat gans on image synthesis
P. Dhariwal and A. Nichol · 2021
Later among the works it cites.
Diffusion probabilistic models for 3d point cloud generation
S. Luo and W. Hu · 2021
Later among the works it cites.
Improved denoising diffusion probabilistic models
A. Q. Nichol and P. Dhariwal · 2021
Later among the works it cites.
Adversarially robust 3d point cloud recognition using self-supervisions
J. Sun, Y. Cao, C. B. Choy, Z. Yu, A. Anandkumar, Z. M. Mao, and C. Xiao · 2021
Later among the works it cites.
J. Sun, A. Mehra, B. Kailkhura, P.-Y. Chen, D. Hendrycks, J. Hamm, and Z. M. Mao · 2021
Later among the works it cites.
Walk in the cloud: Learning curves for point clouds shape analysis
T. Xiang, C. Zhang, Y. Song, J. Yu, and W. Cai · 2021
Later among the works it cites.
Center-based 3d object detection and tracking
T. Yin, X. Zhou, and P. Krähenbühl · 2021
Later among the works it cites.
Emp: Edge-assisted multi-vehicle perception
X. Zhang, A. Zhang, J. Sun, X. Zhu, Y. E. Guo, F. Qian, and Z. M. Mao · 2021
Later among the works it cites.
Point transformer
H. Zhao, L. Jiang, J. Jia, P. H. Torr, and V. Koltun · 2021
Later among the works it cites.
(certified!!) adversarial robustness for free!
N. Carlini, F. Tramer, J. Z. Kolter, et al · 2022
Closest in time.
Robust structured declarative classifiers for 3d point clouds: Defending adversarial attacks with implicit gradients
K. Li, Z. Zhang, C. Zhong, and G. Wang · 2022
Closest in time.
Rethinking network design and local geometry in point cloud: A simple residual mlp framework
X. Ma, C. Qin, H. You, H. Ran, and Y. Fu · 2022
Closest in time.
Diffusion models for adversarial purification
W. Nie, B. Guo, Y. Huang, C. Xiao, A. Vahdat, and A. Anandkumar · 2022
Closest in time.
Benchmarking robustness of 3d point cloud recognition against common corruptions
J. Sun, Q. Zhang, B. Kailkhura, Z. Yu, C. Xiao, and Z. M. Mao · 2022
Closest in time.
On adversarial robustness of trajectory prediction for autonomous vehicles
Q. Zhang, S. Hu, J. Sun, Q. A. Chen, and Z. M. Mao · 2022
Closest in time.