暂无分享,去创建一个
[1] Alexei A. Efros,et al. Ensemble of exemplar-SVMs for object detection and beyond , 2011, 2011 International Conference on Computer Vision.
[2] Tao Xiang,et al. Learning to Compare: Relation Network for Few-Shot Learning , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[3] Andrew Zisserman,et al. An Exemplar Model for Learning Object Classes , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[5] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[6] Stella X. Yu,et al. Unsupervised Feature Learning via Non-parametric Instance Discrimination , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[7] Yann LeCun,et al. Signature Verification Using A "Siamese" Time Delay Neural Network , 1993, Int. J. Pattern Recognit. Artif. Intell..
[8] Jon Louis Bentley,et al. An Algorithm for Finding Best Matches in Logarithmic Expected Time , 1976, TOMS.
[9] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[10] Hugo Larochelle,et al. Optimization as a Model for Few-Shot Learning , 2016, ICLR.
[11] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[12] Navdeep Jaitly,et al. Pointer Networks , 2015, NIPS.
[13] Ming Yang,et al. DeepFace: Closing the Gap to Human-Level Performance in Face Verification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[14] Geoffrey E. Hinton,et al. Neighbourhood Components Analysis , 2004, NIPS.
[15] Cordelia Schmid,et al. Product Quantization for Nearest Neighbor Search , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[16] Hang Li,et al. Meta-SGD: Learning to Learn Quickly for Few Shot Learning , 2017, ArXiv.
[17] Gabriela Csurka,et al. Distance-Based Image Classification: Generalizing to New Classes at Near-Zero Cost , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Alexei A. Efros,et al. Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships , 2009, NIPS.
[19] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[20] Jason Weston,et al. End-To-End Memory Networks , 2015, NIPS.
[21] Oriol Vinyals,et al. Matching Networks for One Shot Learning , 2016, NIPS.
[22] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[24] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Jitendra Malik,et al. SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[26] Kihyuk Sohn,et al. Improved Deep Metric Learning with Multi-class N-pair Loss Objective , 2016, NIPS.
[27] Alexei A. Efros,et al. Recognition by association via learning per-exemplar distances , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[28] Horst Bischof,et al. Large scale metric learning from equivalence constraints , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[30] Bernhard Schölkopf,et al. Estimating the Support of a High-Dimensional Distribution , 2001, Neural Computation.
[31] Xiaogang Wang,et al. Joint Detection and Identification Feature Learning for Person Search , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[33] Alexander J. Smola,et al. Sampling Matters in Deep Embedding Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[34] Geoffrey E. Hinton,et al. Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure , 2007, AISTATS.
[35] Alex Graves,et al. Neural Turing Machines , 2014, ArXiv.
[36] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[37] Alex Pentland,et al. Face recognition using eigenfaces , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[38] Daniel P. Huttenlocher,et al. Pictorial Structures for Object Recognition , 2004, International Journal of Computer Vision.
[39] 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.
[40] Nir Ailon,et al. Deep Metric Learning Using Triplet Network , 2014, SIMBAD.
[41] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Pietro Perona,et al. Unsupervised Learning of Models for Recognition , 2000, ECCV.
[43] Alexei A. Efros,et al. What makes ImageNet good for transfer learning? , 2016, ArXiv.
[44] Jason Weston,et al. Memory Networks , 2014, ICLR.
[45] Yann LeCun,et al. Dimensionality Reduction by Learning an Invariant Mapping , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[46] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[47] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[48] Xing Ji,et al. CosFace: Large Margin Cosine Loss for Deep Face Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[49] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[50] Bartunov Sergey,et al. Meta-Learning with Memory-Augmented Neural Networks , 2016 .
[51] Pieter Abbeel,et al. Meta-Learning with Temporal Convolutions , 2017, ArXiv.
[52] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .