Computer Science ›› 2024, Vol. 51 ›› Issue (4): 254-261.doi: 10.11896/jsjkx.230200140
• Computer Graphics & Multimedia • Previous Articles Next Articles
ZENG Ruiren, XIE Jiangtao, LI Peihua
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[1]LIN T Y,ROYCHOWDHURY A,MAJI S.Bilinear CNN mo-dels for fine-grained visual recognition[C]//Proceedings of the IEEE International Conference on Computer Vision.2015:1449-1457. [2]IONESCU C,VANTZOS O,SMINCHISESCU C.Matrix backpropagation for deep networks with structured layers[C]//Proceedings of the IEEE International Conference on Computer Vision.2015:2965-2973. [3]LI P H,XIE J T,WANG Q L,et al.Is second-order information helpful for large-scale visual recognition[C]//Proceedings of the IEEE International Conference on Computer Vision.2017:2070-2078. [4]LIN T Y,MAJI S.Improved Bilinear Pooling with CNNs[C]//Proceedings of the British Machine Vision Conference.2017:117.1-117.12. [5]DIBA A,SHARMA V,VAN GOOL L.Deep temporal linear encoding networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2017:2329-2338. [6]WINTERBOTTOM T,XIAO S,MCLEAN A,et al.Trying bilinear pooling in Video-QA[J].arXiv:2012.10285,2020. [7]RAHMAN S,WANG L,SUN C,et al.ReDro:Efficiently Lear-ning Large-sized SPD Visual Representation[C]//Computer Vision-ECCV 2020:16th European Conference,Glasgow,UK.Springer International Publishing,2020:1-17. [8]KRAUSE J,STARK M,DENG J,et al.3d object representa-tions for fine-grained categorization[C]//Proceedings of the IEEE International Conference on Computer Vision Workshops.2013:554-561. [9]HIGHAM N J.Functions of matrices:theory and computation[M].Society for Industrial and Applied Mathematics,2008. [10]WANG Q L,XIE J T,ZUO W M,et al.Deep CNNs Meet Glo-bal Covariance Pooling:Better Representation and Generalization[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2021(8):2582-2597. [11]SONG Y,SEBE N,WANG W.Why Approximate MatrixSquare Root Outperforms Accurate SVD in Global Covariance Pooling[C]//Proceedings of the IEEE International Conference on Computer Vision.2021:1115-1123. [12]SONG Y,SEBE N,WANG W.Fast Differentiable MatrixSquare Root[C]//International Conference on Learning Representations.2022. [13]GRETTON A,MAHONEY M W,MOHRI M,et al.Low-rank methods for large-scale machine learning[C]//Neural Information Processing Systems Workshop.2010:40-41. [14]WANG W,DANG Z,HU YL,et al.Backpropagation-friendly eigendecomposition[J].Advances in Neural Information Processing Systems,2019(32):1756-1792. [15]SHLIEN S.A method for computing the partial singular value decomposition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1982(6):671-676. [16]DENG J,DONG W,SOCHER R,et al.Imagenet:A large-scale hierarchical image database[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2009:248-255. [17]CHRABASZCZ P,LOSHCHILOV I,HUTTER F.A downsampled variant of imagenet as an alternative to the cifar datasets[J].arXiv:1707.08819,2017. [18]MAJI S,RAHTU E,KANNALA J,et al.Fine-grained visualclassification of aircraft[J].arXiv:1306.5151,2013. [19]KRAUSE J,STARK M,DENG J,et al.3d object representa-tions for fine-grained categorization[C]//Proceedings of the IEEE International Conference on Computer Vision Workshops.2013:554-561. [20]QUATTONI A,TORRALBA A.Recognizing indoor scenes[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2009:413-420. [21]KRIZHEVSKY A.Learning Multiple Layers of Features fromTiny Images[R].Toronto:University of Toronto,2009. [22]HE K M,ZHANG X Y,REN S Q,et al.Identity mappings in deep residual networks[C]//Computer Vision-ECCV 2016:14th European Conference,Amsterdam,The Netherlands,Part IV 14.Springer International Publishing,2016:630-645. [23]HE K M,ZHANG X Y,REN S Q,et al.Deep residual learning for image recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:770-778. [24]LI P H,XIE J T,WANG Q L,et al.Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2018:947-955. [25]CUI Y,ZHOU F,WANG J,et al.Kernel pooling for convolutional neural networks[C]//Proceedings of the IEEE Confe-rence on Computer Vision and Pattern Recognition.2017:2921-2930. [26]GAO Y,BEIJBOM O,ZHANG N,et al.Compact bilinear pooling[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:317-326. [27]KORSCH D,BODESHEIM P,DENZLER J.Classification-spe-cific parts for improving fine-grained visual categorization[C]//Pattern Recognition:41st DAGM German Conference,DAGM GCPR 2019,Dortmund,Germany.Springer International Publishing,2019:62-75. [28]XIE S N,GIRSHICK R,DOLLAR P,et al.Aggregated residual transformations for deep neural networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2017:1492-1500. [29]IOFFE S,SZEGEDY C.Batch normalization:Accelerating deep network training by reducing internal covariate shift[C]//International Conference on Machine Learning.2015:448-456. [30]HUANG G,LIU Z,VAN DER MAATEN L,et al.Densely connected convolutional networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2017:4700-4708. [31]DOSOVITSKIY A,BEYER L,KOLESNIKOV A,et al.Animage is worth 16x16 words:Transformers for image recognition at scale[C]//International Conference on Learning Representations.2021. |
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