Fetching the paper…
Reading the bibliography…
As 3D point cloud analysis has received increasing attention, the insufficient scale of point cloud datasets and the weak generalization ability of networks become prominent.
Adversarial attack and defense on point sets
Yang, J., Zhang, Q., Fang, R., Ni, B., Liu, J., and Tian, Q · 1902
Earlier work this paper cites.
The earth mover’s distance as a metric for image retrieval
Rubner, Y., Tomasi, C., and Guibas, L. J · 2000
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
Geiger, A., Lenz, P., and Urtasun, R · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
Earlier work this paper cites.
3d shapenets: A deep representation for volumetric shapes
Wu, Z., Song, S., Khosla, A., Yu, F., Zhang, L., Tang, X., and Xiao, J · 2015
Earlier work this paper cites.
A scalable active framework for region annotation in 3d shape collections
Yi, L., Kim, V. G., Ceylan, D., Shen, I.-C., Yan, M., Su, H., Lu, C., Huang, Q., Sheffer, A., and Guibas, L · 2016
Earlier work this paper cites.
Automatic differentiation in pytorch
Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A · 2017
Earlier work this paper cites.
Threat of adversarial attacks on deep learning in computer vision: A survey
Akhtar, N. and Mian, A · 2018
Earlier work this paper cites.
Boosting adversarial attacks with momentum
Dong, Y., Liao, F., Pang, T., Su, H., Zhu, J., Hu, X., and Li, J · 2018
Earlier work this paper cites.
Rgcnn: Regularized graph cnn for point cloud segmentation
Te, G., Hu, W., Zheng, A., and Guo, Z · 2018
Earlier work this paper cites.
Local spectral graph convolution for point set feature learning
Wang, C., Samari, B., and Siddiqi, K · 2018
Earlier work this paper cites.
mixup: Beyond empirical risk minimization
Zhang, H., Cisse, M., Dauphin, Y. N., and Lopez-Paz, D · 2018
Earlier work this paper cites.
Fast point r-cnn
Chen, Y., Liu, S., Shen, X., and Jia, J · 2019
Earlier work this paper cites.
Mixup as locally linear out-of-manifold regularization
Guo, H., Mao, Y., and Zhang, R · 2019
Earlier work this paper cites.
Bag of tricks for image classification with convolutional neural networks
He, T., Zhang, Z., Zhang, H., Zhang, Z., Xie, J., and Li, M · 2019
Cited alongside, same era.
Pointpillars: Fast encoders for object detection from point clouds
Lang, A. H., Vora, S., Caesar, H., Zhou, L., Yang, J., and Beijbom, O · 2019
Cited alongside, same era.
Kpconv: Flexible and deformable convolution for point clouds
Thomas, H., Qi, C. R., Deschaud, J.-E., Marcotegui, B., Goulette, F., and Guibas, L. J · 2019
Cited alongside, same era.
Manifold mixup: Better representations by interpolating hidden states
Verma, V., Lamb, A., Beckham, C., Najafi, A., Mitliagkas, I., Lopez-Paz, D., and Bengio, Y · 2019
Cited alongside, same era.
Dynamic graph cnn for learning on point clouds
Wang, Y., Sun, Y., Liu, Z., Sarma, S. E., Bronstein, M. M., and Solomon, J. M · 2019
Cited alongside, same era.
Generating 3d adversarial point clouds
Xiang, C., Qi, C. R., and Li, B · 2019
Advpc: Transferable adversarial perturbations on 3d point clouds
Hamdi, A., Rojas, S., Thabet, A., and Ghanem, B · 2020
Later among the works it cites.
Fmix: Enhancing mixed sample data augmentation
Harris, E., Marcu, A., Painter, M., Niranjan, M., and Hare, A. P.-B. J · 2020
Later among the works it cites.
Self-supervised visual feature learning with deep neural networks: A survey
Jing, L. and Tian, Y · 2020
Later among the works it cites.
Pointaugment: an auto-augmentation framework for point cloud classification
Li, R., Li, X., Heng, P.-A., and Fu, C.-W · 2020
Later among the works it cites.
Global-local bidirectional reasoning for unsupervised representation learning of 3d point clouds
Rao, Y., Lu, J., and Zhou, J · 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…
Cited alongside, same era.
Cutmix: Regularization strategy to train strong classifiers with localizable features
Yun, S., Han, D., Oh, S. J., Chun, S., Choe, J., and Yoo, Y · 2019
Cited alongside, same era.
Pointweb: Enhancing local neighborhood features for point cloud processing
Zhao, H., Jiang, L., Fu, C.-W., and Jia, J · 2019
Cited alongside, same era.
Pointcloud saliency maps
Zheng, T., Chen, C., Yuan, J., Li, B., and Ren, K · 2019
Cited alongside, same era.
Dup-net: Denoiser and upsampler network for 3d adversarial point clouds defense
Zhou, H., Chen, K., Zhang, W., Fang, H., Zhou, W., and Yu, N · 2019
Cited alongside, same era.
Deformable pv-rcnn: Improving 3d object detection with learned deformations
Bhattacharyya, P. and Czarnecki, K · 2020
Cited alongside, same era.
Pointmixup: Augmentation for point clouds
Chen, Y., Hu, V. T., Gavves, E., Mensink, T., Mettes, P., Yang, P., and Snoek, C. G · 2020
Cited alongside, same era.
Shi, S., Guo, C., Jiang, L., Wang, Z., Shi, J., Wang, X., and Li, H · 2020
Later among the works it cites.
Pointmask: Towards interpretable and bias-resilient point cloud processing
Taghanaki, S. A., Hassani, K., Jayaraman, P. K., Khasahmadi, A. H., and Custis, T · 2020
Later among the works it cites.
Robust adversarial objects against deep learning models
Tsai, T., Yang, K., Ho, T.-Y., and Jin, Y · 2020
Later among the works it cites.
Attentive cutmix: An enhanced data augmentation approach for deep learning based image classification
Walawalkar, D., Shen, Z., Liu, Z., and Savvides, M · 2020
Later among the works it cites.
If-defense: 3d adversarial point cloud defense via implicit function based restoration
Wu, Z., Duan, Y., Wang, H., Fan, Q., and Guibas, L. J · 2020
Later among the works it cites.
Weakly supervised semantic point cloud segmentation: Towards 10x fewer labels
Xu, X. and Lee, G. H · 2020
Later among the works it cites.
Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling
Yan, X., Zheng, C., Li, Z., Wang, S., and Cui, S · 2020
Later among the works it cites.
On isometry robustness of deep 3d point cloud models under adversarial attacks
Zhao, Y., Wu, Y., Chen, C., and Lim, A · 2020
Later among the works it cites.
Zhou, H., Chen, D., Liao, J., Chen, K., Dong, X., Liu, K., Zhang, W., Hua, G., and Yu, N · 2020
Later among the works it cites.