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Traditional recognition methods typically require large, artificially-balanced training classes, while few-shot learning methods are tested on artificially small ones.
Visual categorization with bags of keypoints
G. Csurka, C. R. Dance, L. Fan, J. Willamowski, and C. Bray · 2004
Earlier work this paper cites.
Object classification from a single example utilizing class relevance metrics
M. Fink · 2004
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
Earlier work this paper cites.
Aggregating local descriptors into a compact image representation
H. Jégou, M. Douze, C. Schmid, and P. Pérez · 2010
Earlier work this paper cites.
Improving the fisher kernel for large-scale image classification
F. Perronnin, J. Sánchez, and T. Mensink · 2010
Earlier work this paper cites.
Sun database: Large-scale scene recognition from abbey to zoo
J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba · 2010
Earlier work this paper cites.
Semantic segmentation with second-order pooling
J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu · 2012
Earlier work this paper cites.
Segmentation propagation in imagenet
D. Kuettel, M. Guillaumin, and V. Ferrari · 2012
Earlier work this paper cites.
Imagenet auto-annotation with segmentation propagation
M. Guillaumin, D. Küttel, and V. Ferrari · 2014
Earlier work this paper cites.
Microsoft COCO: common objects in context
T. Lin, M. Maire, S. J. Belongie, L. D. Bourdev, R. B. Girshick, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Earlier work this paper cites.
Learning deep features for scene recognition using places database
B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva · 2014
Earlier work this paper cites.
Material recognition in the wild with the materials in context database
S. Bell, P. Upchurch, N. Snavely, and K. Bala · 2015
Earlier work this paper cites.
An exploration of parameter redundancy in deep networks with circulant projections
Y. Cheng, F. X. Yu, R. S. Feris, S. Kumar, A. Choudhary, and S.-F. Chang · 2015
Earlier work this paper cites.
Siamese neural networks for one-shot image recognition
G. Koch, R. Zemel, and R. Salakhutdinov · 2015
Earlier work this paper cites.
Human-level concept learning through probabilistic program induction
B. M. Lake, R. Salakhutdinov, and J. B. Tenenbaum · 2015
Earlier work this paper cites.
Is object localization for free? - weakly-supervised learning with convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2015
Earlier work this paper cites.
The application of two-level attention models in deep convolutional neural network for fine-grained image classification
T. Xiao, Y. Xu, K. Yang, J. Zhang, Y. Peng, and Z. Zhang · 2015
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Deep fried convnets
Z. Yang, M. Moczulski, M. Denil, N. d. Freitas, A. Smola, L. Song, and Z. Wang · 2015
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Learning feed-forward one-shot learners
L. Bertinetto, J. a. F. Henriques, J. Valmadre, P. H. S. Torr, and A. Vedaldi · 2016
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One-to-many face recognition with bilinear cnns
A. R. Chowdhury, T. Lin, S. Maji, and E. Learned-Miller · 2016
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Compact bilinear pooling
Y. Gao, O. Beijbom, N. Zhang, and T. Darrell · 2016
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Deepfashion: Powering robust clothes recognition and retrieval with rich annotations
Z. Liu, P. Luo, S. Qiu, X. Wang, and X. Tang · 2016
Cited alongside, same era.
Meta networks
T. Munkhdalai and H. Yu · 2017
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Extreme clicking for efficient object annotation
D. P. Papadopoulos, J. R. R. Uijlings, F. Keller, and V. Ferrari · 2017
Later among the works it cites.
Optimization as a model for few-shot learning
S. Ravi and H. Larochelle · 2017
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One-shot learning for semantic segmentation
A. Shaban, S. Bansal, Z. Liu, I. Essa, and B. Boots · 2017
Later among the works it cites.
Prototypical networks for few-shot learning
J. Snell, K. Swersky, and R. S. Zemel · 2017
Later among the works it cites.
Residual attention network for image classification
F. Wang, M. Jiang, C. Qian, S. Yang, C. Li, H. Zhang, X. Wang, and X. Tang · 2017
Later among the works it cites.
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Meta-learning with memory-augmented neural networks
A. Santoro, S. Bartunov, M. Botvinick, D. Wierstra, and T. Lillicrap · 2016
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Matching networks for one shot learning
O. Vinyals, C. Blundell, T. Lillicrap, k. kavukcuoglu, and D. Wierstra · 2016
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Learning to learn: Model regression networks for easy small sample learning
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Learning deep features for discriminative localization
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2016
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Towards a neural statistician
H. Edwards and A. Storkey · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
C. Finn, P. Abbeel, and S. Levine · 2017
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Y. Wang, D. K. Ramanan, and M. Hebert · 2017
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https://docs.scipy.org/doc/numpy-1.15.0/user/basics.broadcasting.html
Broadcasting - numpy v1.15 manual · 2018
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https://pytorch.org/docs/stable/notes/broadcasting.html
Broadcasting semantics - pytorch master documentation · 2018
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https://www.tensorflow.org/xla/broadcasting
Broadcasting semantics — xla — tensorflow · 2018
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Covariance pooling for facial expression recognition
D. Acharya, Z. Huang, D. Pani Paudel, and L. Van Gool · 2018
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A simple neural attentive meta-learner
N. Mishra, M. Rohaninejad, X. Chen, and P. Abbeel · 2018
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Deep covariance descriptors for facial expression recognition
N. Otberdout, A. Kacem, M. Daoudi, L. Ballihi, and S. Berretti · 2018
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Learning to compare: Relation network for few-shot learning
F. Sung, Y. Yang, L. Zhang, T. Xiang, P. H. Torr, and T. M. Hospedales · 2018
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The inaturalist species classification and detection dataset
G. Van Horn, O. Mac Aodha, Y. Song, Y. Cui, C. Sun, A. Shepard, H. Adam, P. Perona, and S. Belongie · 2018
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Low-shot learning from imaginary data
Y. xiong Wang, R. Girshick, M. Herbert, and B. Hariharan · 2018
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Power normalizing second-order similarity network for few-shot learning
H. Zhang and P. Koniusz · 2019
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