Nguyen A, Yosinski J, Clune J. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015: 427-436.
(ECCV 2018) Group normalization
Keyword [Group Normalization]
Wu Y, He K. Group normalization[C]//Proceedings of the European Conference on Computer Vision (ECCV). 2018: 3-19.
(2017) Paying more attention to attention:Improving the performance of convolutional neural networks via attention transfer
Keyword [Attention Map]
Zagoruyko S, Komodakis N. Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer[J]. arXiv preprint arXiv:1612.03928, 2016.
(ECCV 2014) Visualizing and understanding convolutional networks
Zeiler M D, Fergus R. Visualizing and understanding convolutional networks[C]//European conference on computer vision. Springer, Cham, 2014: 818-833
(ICCV 2017) SO-Net:Self-Organizing Network for Point Cloud Analysis
Li J, Chen B M, Hee Lee G. So-net: Self-organizing network for point cloud analysis[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 9397-9406.
(ICCV 2017) Escape from cells:Deep kd-networks for the recognition of 3d point cloud models
Klokov R, Lempitsky V. Escape from cells: Deep kd-networks for the recognition of 3d point cloud models[C]//2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017: 863-872.
(CVPR 2018) Frustum pointnets for 3d object detection from rgb-d data
Qi C R, Liu W, Wu C, et al. Frustum pointnets for 3d object detection from rgb-d data[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018: 918-927.
(NIPS 2017) Pointnet++:Deep hierarchical feature learning on point sets in a metric space
Qi C R, Yi L, Su H, et al. Pointnet++: Deep hierarchical feature learning on point sets in a metric space[C]//Advances in Neural Information Processing Systems. 2017: 5105-5114.
(CVPR 2017) Pointnet:Deep learning on point sets for 3d classification and segmentation
Qi C R, Su H, Mo K, et al. Pointnet: Deep learning on point sets for 3d classification and segmentation[J]. Proc. Computer Vision and Pattern Recognition (CVPR), IEEE, 2017, 1(2): 4.
(CVPR 2018) Cascaded Pyramid Network for Multi-Person Pose Estimation
Keyword [CPN]
Chen Y, Wang Z, Peng Y, et al. Cascaded pyramid network for multi-person pose estimation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018: 7103-7112.