Factorized Bilinear Models for Image Recognition
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Jiaying Liu | Naiyan Wang | Yanghao Li | Xiaodi Hou | Naiyan Wang | Xiaodi Hou | Jiaying Liu | Yanghao Li
[1] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[2] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[3] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[4] Yang Gao,et al. Compact Bilinear Pooling , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Iasonas Kokkinos,et al. Describing Textures in the Wild , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[6] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[8] Zhuowen Tu,et al. Deeply-Supervised Nets , 2014, AISTATS.
[9] Gregory Shakhnarovich,et al. FractalNet: Ultra-Deep Neural Networks without Residuals , 2016, ICLR.
[10] Peter Kontschieder,et al. Deep Neural Decision Forests , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[11] Subhransu Maji,et al. One-to-many face recognition with bilinear CNNs , 2015, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
[12] Steffen Rendle,et al. Factorization Machines , 2010, 2010 IEEE International Conference on Data Mining.
[13] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[14] Rasmus Pagh,et al. Fast and scalable polynomial kernels via explicit feature maps , 2013, KDD.
[15] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[16] Yoshua Bengio,et al. FitNets: Hints for Thin Deep Nets , 2014, ICLR.
[17] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[18] John Tran,et al. cuDNN: Efficient Primitives for Deep Learning , 2014, ArXiv.
[19] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[20] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[22] Nanning Zheng,et al. Similarity learning on an explicit polynomial kernel feature map for person re-identification , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Harish Karnick,et al. Random Feature Maps for Dot Product Kernels , 2012, AISTATS.
[24] Andrew Zisserman,et al. Return of the Devil in the Details: Delving Deep into Convolutional Nets , 2014, BMVC.
[25] Zheng Zhang,et al. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems , 2015, ArXiv.
[26] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Kilian Q. Weinberger,et al. Deep Networks with Stochastic Depth , 2016, ECCV.
[28] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[29] Nikos Komodakis,et al. Wide Residual Networks , 2016, BMVC.
[30] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[31] Qiang Chen,et al. Network In Network , 2013, ICLR.
[32] Subhransu Maji,et al. Bilinear CNN Models for Fine-Grained Visual Recognition , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[33] Sepp Hochreiter,et al. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) , 2015, ICLR.
[34] Jürgen Schmidhuber,et al. Training Very Deep Networks , 2015, NIPS.
[35] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Li Xu,et al. On Vectorization of Deep Convolutional Neural Networks for Vision Tasks , 2015, AAAI.
[37] Yangqing Jia,et al. Learning Semantic Image Representations at a Large Scale , 2014 .
[38] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[39] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[40] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[41] Cristian Sminchisescu,et al. Semantic Segmentation with Second-Order Pooling , 2012, ECCV.
[42] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.