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Point cloud is an important 3D data representation widely used in many essential applications.
Marching Cubes: A high resolution 3D surface construction algorithm
William E Lorensen and Harvey E Cline · 1987
Earlier work this paper cites.
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Explaining and Harnessing Adversarial Examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Ba · 2014
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ShapeNet: An Information-Rich 3D Model Repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
Earlier work this paper cites.
3D ShapeNets: A Deep Representation for Volumetric Shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
Earlier work this paper cites.
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard · 2016
Earlier work this paper cites.
Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks
Nicolas Papernot, Patrick McDaniel, Xi Wu, Somesh Jha, and Ananthram Swami · 2016
Earlier work this paper cites.
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini and David Wagner · 2017
Earlier work this paper cites.
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
Earlier work this paper cites.
Universal Adversarial Perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
Earlier work this paper cites.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Mitigating Adversarial Effects Through Randomization
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, and Alan Yuille · 2017
Earlier work this paper cites.
Learning Representations and Generative Models for 3D Point Clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
Earlier work this paper cites.
Synthesizing Robust Adversarial Examples
Anish Athalye, Logan Engstrom, Andrew Ilyas, and Kevin Kwok · 2018
Earlier work this paper cites.
Monte Carlo Convolution for Learning on Non-Uniformly Sampled Point Clouds
Pedro Hermosilla, Tobias Ritschel, Pere-Pau Vázquez, Àlvar Vinacua, and Timo Ropinski · 2018
Cited alongside, same era.
Deep Marching Cubes: Learning Explicit Surface Representations
Y. Liao, S. Donne, and A. Geiger · 2018
Cited alongside, same era.
PU-Net: Point Cloud Upsampling Network
Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, and Pheng-Ann Heng · 2018
Cited alongside, same era.
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Yulong Cao, Chaowei Xiao, Dawei Yang, Jing Fang, Ruigang Yang, Mingyan Liu, and Bo Li · 2019
Cited alongside, same era.
On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian Goodfellow, Aleksander Madry, and Alexey Kurakin · 2019
Cited alongside, same era.
PointConv: Deep Convolutional Networks on 3D Point Clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 2019
Later among the works it cites.
Generating 3D Adversarial Point Clouds
Chong Xiang, Charles R Qi, and Bo Li · 2019
Later among the works it cites.
Adversarial Attack and Defense on Point Sets
Jiancheng Yang, Qiang Zhang, Rongyao Fang, Bingbing Ni, Jinxian Liu, and Qi Tian · 2019
Later among the works it cites.
PointCloud Saliency Maps
Tianhang Zheng, Changyou Chen, Junsong Yuan, Bo Li, and Kui Ren · 2019
Later among the works it cites.
DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense
Hang Zhou, Kejiang Chen, Weiming Zhang, Han Fang, Wenbo Zhou, and Nenghai Yu · 2019
Later among the works it cites.
Self-Robust 3D Point Recognition via Gather-Vector Guidance
Xiaoyi Dong, Dongdong Chen, Hang Zhou, Gang Hua, Weiming Zhang, and Nenghai Yu · 2020
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Learning Implicit Fields for Generative Shape Modeling
Zhiqin Chen and Hao Zhang · 2019
Cited alongside, same era.
Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning
Pedro Hermosilla, Tobias Ritschel, and Timo Ropinski · 2019
Cited alongside, same era.
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers
Daniel Liu, Ronald Yu, and Hao Su · 2019
Cited alongside, same era.
Relation-Shape Convolutional Neural Network for Point Cloud Analysis
Yongcheng Liu, Bin Fan, Shiming Xiang, and Chunhong Pan · 2019
Cited alongside, same era.
Occupancy Networks: Learning 3D Reconstruction in Function Space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Implicit Surface Representations As Layers in Neural Networks
Mateusz Michalkiewicz, Jhony K Pontes, Dominic Jack, Mahsa Baktashmotlagh, and Anders Eriksson · 2019
Cited alongside, same era.
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Cited alongside, same era.
Closest in time.
Curriculum DeepSDF
Yueqi Duan, Haidong Zhu, He Wang, Li Yi, Ram Nevatia, and Leonidas J Guibas · 2020
Closest in time.
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds
Abdullah Hamdi, Sara Rojas, Ali Thabet, and Bernard Ghanem · 2020
Closest in time.
Point2Mesh: A Self-Prior for Deformable Meshes
R. Hanocka, G. Metzer, R. Giryes, and D. Cohen-Or · 2020
Closest in time.
Convolutional Occupancy Networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
Closest in time.
Learning Graph-Convolutional Representations for Point Cloud Denoising
Francesca Pistilli, Giulia Fracastoro, Diego Valsesia, and Enrico Magli · 2020
Closest in time.
PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds
Marie-Julie Rakotosaona, Vittorio La Barbera, Paul Guerrero, Niloy J Mitra, and Maks Ovsjanikov · 2020
Closest in time.
Robust Adversarial Objects against Deep Learning Models
Tzungyu Tsai, Kaichen Yang, Tsung-Yi Ho, and Yier Jin · 2020
Closest in time.
Physically Realizable Adversarial Examples for LiDAR Object Detection
James Tu, Mengye Ren, Sivabalan Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, and Raquel Urtasun · 2020
Closest in time.
LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud Based Deep Networks
Hang Zhou, Dongdong Chen, Jing Liao, Kejiang Chen, Xiaoyi Dong, Kunlin Liu, Weiming Zhang, Gang Hua, and Nenghai Yu · 2020
Closest in time.