Collect and Select: Semantic Alignment Metric Learning for Few-Shot Learning
暂无分享,去创建一个
Dacheng Tao | Jun Cheng | Lei Wang | Fusheng Hao | Fengxiang He | Jianzhong Cao | D. Tao | Jun Cheng | Fengxiang He | Fusheng Hao | Lei Wang | Jianzhong Cao
[1] Tao Xiang,et al. Learning to Compare: Relation Network for Few-Shot Learning , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[2] Sergey Levine,et al. Probabilistic Model-Agnostic Meta-Learning , 2018, NeurIPS.
[3] Joan Bruna,et al. Few-Shot Learning with Graph Neural Networks , 2017, ICLR.
[4] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[5] Bernhard Schölkopf,et al. Discriminative k-shot learning using probabilistic models , 2017, ArXiv.
[6] Ali Borji,et al. Salient Object Detection: A Benchmark , 2015, IEEE Transactions on Image Processing.
[7] Renjie Liao,et al. Incremental Few-Shot Learning with Attention Attractor Networks , 2018, NeurIPS.
[8] Nikos Komodakis,et al. Wide Residual Networks , 2016, BMVC.
[9] Wei Shen,et al. Few-Shot Image Recognition by Predicting Parameters from Activations , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[10] Matus Telgarsky,et al. Spectrally-normalized margin bounds for neural networks , 2017, NIPS.
[11] Philip H. S. Torr,et al. Learn To Pay Attention , 2018, ICLR.
[12] Xuming He,et al. A Dual Attention Network with Semantic Embedding for Few-Shot Learning , 2019, AAAI.
[13] Hugo Larochelle,et al. Optimization as a Model for Few-Shot Learning , 2016, ICLR.
[14] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[15] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[16] Tsendsuren Munkhdalai,et al. Rapid Adaptation with Conditionally Shifted Neurons , 2017, ICML.
[17] Pieter Abbeel,et al. A Simple Neural Attentive Meta-Learner , 2017, ICLR.
[18] Nikos Komodakis,et al. Dynamic Few-Shot Visual Learning Without Forgetting , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[19] Subhransu Maji,et al. Improved Bilinear Pooling with CNNs , 2017, BMVC.
[20] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[21] Razvan Pascanu,et al. Meta-Learning with Latent Embedding Optimization , 2018, ICLR.
[22] Nikos Komodakis,et al. Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer , 2016, ICLR.
[23] Martial Hebert,et al. Low-Shot Learning from Imaginary Data , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[24] Yu-Chiang Frank Wang,et al. A Closer Look at Few-shot Classification , 2019, ICLR.
[25] Joshua Achiam,et al. On First-Order Meta-Learning Algorithms , 2018, ArXiv.
[26] Yoshua Bengio,et al. MetaGAN: An Adversarial Approach to Few-Shot Learning , 2018, NeurIPS.
[27] Oriol Vinyals,et al. Matching Networks for One Shot Learning , 2016, NIPS.
[28] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[29] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Thomas L. Griffiths,et al. Recasting Gradient-Based Meta-Learning as Hierarchical Bayes , 2018, ICLR.
[31] Yongxin Yang,et al. Deep Comparison: Relation Columns for Few-Shot Learning , 2018, ArXiv.
[32] Ameet Talwalkar,et al. Foundations of Machine Learning , 2012, Adaptive computation and machine learning.
[33] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[34] Tsendsuren Munkhdalai,et al. Learning Rapid-Temporal Adaptations , 2017, ArXiv.
[35] Lei Wang,et al. Anchor-based Nearest Class Mean Loss for Convolutional Neural Networks , 2018, ArXiv.
[36] Hang Li,et al. Meta-SGD: Learning to Learn Quickly for Few Shot Learning , 2017, ArXiv.
[37] Alexandre Lacoste,et al. TADAM: Task dependent adaptive metric for improved few-shot learning , 2018, NeurIPS.
[38] Abhinav Gupta,et al. Non-local Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[39] Gregory R. Koch,et al. Siamese Neural Networks for One-Shot Image Recognition , 2015 .
[40] Gang Yu,et al. Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation , 2019, AAAI.
[41] Jian Cheng,et al. Additive Margin Softmax for Face Verification , 2018, IEEE Signal Processing Letters.
[42] Ambedkar Dukkipati,et al. Generative Adversarial Residual Pairwise Networks for One Shot Learning , 2017, ArXiv.
[43] Bharath Hariharan,et al. Low-Shot Visual Recognition by Shrinking and Hallucinating Features , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[44] Tao Mei,et al. Memory Matching Networks for One-Shot Image Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[45] Pietro Perona,et al. One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.