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In state-of-the-art deep neural networks, both feature normalization and feature attention have become ubiquitous.
1903
Earlier work this paper cites.
1905
Earlier work this paper cites.
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Neural Information Processing Systems (NIPS). pp. 1106–1114 (2012)
2012
Earlier work this paper cites.
2014
Earlier work this paper cites.
Girshick, R.: Fast R-CNN. In: Proceedings of the International Conference on Computer Vision (ICCV) (2015)
2015
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In: 2015 IEEE International Conference on Computer Vision, ICCV 2015, Santiago, Chile, December 7-13, 2015. pp. 1026–1034 (2015). https://doi.org/10.1109/ICCV.2015.123, https://doi.org/10.1109/ICCV.2015.123
2015
Earlier work this paper cites.
Ioffe, S., Szegedy, C.: Batch normalization: Accelerating deep network training by reducing internal covariate shift. In: Blei, D., Bach, F. (eds.) Proceedings of the 32nd International Conference on Machine Learning (ICML-15). pp. 448–456. JMLR Workshop and Conference Proceedings (2015), http://jmlr.org/proceedings/papers/v37/ioffe15.pdf
2015
Earlier work this paper cites.
Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: Towards real-time object detection with region proposal networks. In: Neural Information Processing Systems (NIPS) (2015)
2015
Earlier work this paper cites.
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: ImageNet Large Scale Visual Recognition Challenge. Int. J. Comput. Vision (IJCV) 115
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Ba, L.J., Kiros, R., Hinton, G.E.: Layer normalization. CoRR abs/1607.06450
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
2016
Earlier work this paper cites.
Loshchilov, I., Hutter, F.: SGDR: stochastic gradient descent with restarts. CoRR abs/1608.03983
2016
Earlier work this paper cites.
Salimans, T., Kingma, D.P.: Weight normalization: A simple reparameterization to accelerate training of deep neural networks. In: Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain. p. 901 (2016)
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
He, K., Gkioxari, G., Dollár, P., Girshick, R.B.: Mask R-CNN. In: IEEE International Conference on Computer Vision, ICCV 2017, Venice, Italy, October 22-29, 2017. pp. 2980–2988 (2017). https://doi.org/10.1109/ICCV.2017.322, https://doi.org/10.1109/ICCV.2017.322
2017
Cited alongside, same era.
Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. CoRR abs/1709.01507
2017
Cited alongside, same era.
Huang, G., Liu, Z., van der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)
2017
Cited alongside, same era.
Ioffe, S.: Batch renormalization: Towards reducing minibatch dependence in batch-normalized models. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA. pp. 1945–1953 (2017)
2017
Miyato, T., Koyama, M.: cgans with projection discriminator. arXiv preprint arXiv:1802.05637 (2018)
2018
Later among the works it cites.
Peng, C., Xiao, T., Li, Z., Jiang, Y., Zhang, X., Jia, K., Yu, G., Sun, J.: Megdet: A large mini-batch object detector. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18-22, 2018. pp. 6181–6189 (2018)
2018
Later among the works it cites.
Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: Mobilenetv2: Inverted residuals and linear bottlenecks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 4510–4520 (2018)
2018
Later among the works it cites.
Santurkar, S., Tsipras, D., Ilyas, A., Madry, A.: How does batch normalization help optimization? In: Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December 2018, Montréal, Canada. pp. 2488–2498 (2018), http://papers.nips.cc/paper/7515-how-does-batch-normalization-help-optimization
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Cited alongside, same era.
Lin, T., Dollár, P., Girshick, R.B., He, K., Hariharan, B., Belongie, S.J.: Feature pyramid networks for object detection. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017. pp. 936–944 (2017). https://doi.org/10.1109/CVPR.2017.106, https://doi.org/10.1109/CVPR.2017.106
2017
Cited alongside, same era.
2017
Cited alongside, same era.
de Vries, H., Strub, F., Mary, J., Larochelle, H., Pietquin, O., Courville, A.C.: Modulating early visual processing by language. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA. pp. 6597–6607 (2017), http://papers.nips.cc/paper/7237-modulating-early-visual-processing-by-language
2017
Cited alongside, same era.
Wang, F., Jiang, M., Qian, C., Yang, S., Li, C., Zhang, H., Wang, X., Tang, X.: Residual attention network for image classification. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017. pp. 6450–6458 (2017). https://doi.org/10.1109/CVPR.2017.683, https://doi.org/10.1109/CVPR.2017.683
2017
Cited alongside, same era.
2018
Cited alongside, same era.
Cai, Z., Vasconcelos, N.: Cascade R-CNN: delving into high quality object detection. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18-22, 2018. pp. 6154–6162 (2018). https://doi.org/10.1109/CVPR.2018.00644, http://openaccess.thecvf.com/content_cvpr_2018/html/Cai_Cascade_R-CNN_Delving_CVPR_2018_paper.html
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Huang, L., Liu, X., Lang, B., Yu, A.W., Wang, Y., Li, B.: Orthogonal weight normalization: Solution to optimization over multiple dependent stiefel manifolds in deep neural networks. In: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018. pp. 3271–3278 (2018), https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17072
2018
Cited alongside, same era.
2018
Later among the works it cites.
Wang, X., Girshick, R.B., Gupta, A., He, K.: Non-local neural networks. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18-22, 2018. pp. 7794–7803 (2018). https://doi.org/10.1109/CVPR.2018.00813, http://openaccess.thecvf.com/content_cvpr_2018/html/Wang_Non-Local_Neural_Networks_CVPR_2018_paper.html
2018
Later among the works it cites.
Woo, S., Park, J., Lee, J., Kweon, I.S.: CBAM: convolutional block attention module. In: Computer Vision - ECCV 2018 - 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part VII. pp. 3–19 (2018). https://doi.org/10.1007/978-3-030-01234-2_1, https://doi.org/10.1007/978-3-030-01234-2_1
2018
Later among the works it cites.
Wu, Y., He, K.: Group normalization. In: Computer Vision - ECCV 2018 - 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XIII. pp. 3–19 (2018). https://doi.org/10.1007/978-3-030-01261-8_1, https://doi.org/10.1007/978-3-030-01261-8_1
2018
Later among the works it cites.
Zhang, H., Cissé, M., Dauphin, Y.N., Lopez-Paz, D.: mixup: Beyond empirical risk minimization. In: 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings (2018), https://openreview.net/forum?id=r1Ddp1-Rb
2018
Later among the works it cites.
2019
Closest in time.
Deecke, L., Murray, I., Bilen, H.: Mode normalization. In: 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019 (2019), https://openreview.net/forum?id=HyN-M2Rctm
2019
Closest in time.
Jia, S., Chen, D., Chen, H.: Instance-level meta normalization. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019. pp. 4865–4873 (2019), http://openaccess.thecvf.com/content_CVPR_2019/html/Jia_Instance-Level_Meta_Normalization_CVPR_2019_paper.html
2019
Closest in time.
Kalayeh, M.M., Shah, M.: Training faster by separating modes of variation in batch-normalized models. IEEE Transactions on Pattern Analysis and Machine Intelligence pp. 1–1 (2019). https://doi.org/10.1109/TPAMI.2019.2895781
2019
Closest in time.
Li, X., Song, X., Wu, T.: Aognets: Compositional grammatical architectures for deep learning. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019. pp. 6220–6230 (2019)
2019
Closest in time.
Pan, X., Zhan, X., Shi, J., Tang, X., Luo, P.: Switchable whitening for deep representation learning. In: 2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019. pp. 1863–1871. IEEE (2019). https://doi.org/10.1109/ICCV.2019.00195, https://doi.org/10.1109/ICCV.2019.00195
2019
Closest in time.
Park, T., Liu, M., Wang, T., Zhu, J.: Semantic image synthesis with spatially-adaptive normalization. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019. pp. 2337–2346 (2019)
2019
Closest in time.
Sun, W., Wu, T.: Image synthesis from reconfigurable layout and style. In: International Conference on Computer Vision, ICCV (2019)
2019
Closest in time.