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Proxy-based metric learning losses are superior to pair-based losses due to their fast convergence and low training complexity.
Learning internal representations by error propagation
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Dimensionality reduction by learning an invariant mapping
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Visualizing data using t-sne
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A robust em clustering algorithm for gaussian mixture models
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3d object representations for fine-grained categorization
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Hd-cnn: hierarchical deep convolutional neural networks for large scale visual recognition
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deepfashion: Powering robust clothes recognition and retrieval with rich annotations
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Deep decision network for multi-class image classification
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Deep metric learning via lifted structured feature embedding
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Beyond triplet loss: a deep quadruplet network for person re-identification
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No fuss distance metric learning using proxies
Yair Movshovitz-Attias, Alexander Toshev, Thomas K Leung, Sergey Ioffe, and Saurabh Singh · 2017
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Sampling matters in deep embedding learning
Chao-Yuan Wu, R Manmatha, Alexander J Smola, and Philipp Krahenbuhl · 2017
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Deep metric learning with hierarchical triplet loss
Weifeng Ge, Weilin Huang, Dengke Dong, and Matthew R Scott · 2018
Divide and conquer the embedding space for metric learning
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Multi-similarity loss with general pair weighting for deep metric learning
Xun Wang, Xintong Han, Weilin Huang, Dengke Dong, and Matthew R Scott · 2019
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A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses
Malik Boudiaf, Jérôme Rony, Imtiaz Masud Ziko, Eric Granger, Marco Pedersoli, Pablo Piantanida, and Ismail Ben Ayed · 2020
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Smooth-ap: Smoothing the path towards large-scale image retrieval
Andrew Brown, Weidi Xie, Vicky Kalogeiton, and Andrew Zisserman · 2020
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The group loss for deep metric learning
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Proxy anchor loss for deep metric learning
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Reducing class collapse in metric learning with easy positive sampling
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Diva: Diverse visual feature aggregation for deep metric learning
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A metric learning reality check
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Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis
Eu Wern Teh, Terrance DeVries, and Graham W Taylor · 2020
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Cross-batch memory for embedding learning
Xun Wang, Haozhi Zhang, Weilin Huang, and Matthew R Scott · 2020
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Online deep clustering for unsupervised representation learning
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