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The significant amount of training data required for training Convolutional Neural Networks has become a bottleneck for applications like semantic segmentation.
A perspective view and survey of meta-learning
Vilalta, R.; and Drissi, Y. 2002 · 2002
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Part-aware Prototype Network for Few-shot Semantic Segmentation
Liu, Y.; Zhang, X.; Zhang, S.; and He, X. 2020 · 2007
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The pascal visual object classes (voc) challenge
Everingham, M.; Van Gool, L.; Williams, C. K.; Winn, J.; and Zisserman, A. 2010 · 2010
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Semantic contours from inverse detectors
Hariharan, B.; Arbeláez, P.; Bourdev, L.; Maji, S.; and Malik, J. 2011 · 2011
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Distributed representations of words and phrases and their compositionality
Mikolov, T.; Sutskever, I.; Chen, K.; Corrado, G. S.; and Dean, J. 2013 · 2013
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Fully convolutional networks for semantic segmentation
Long, J.; Shelhamer, E.; and Darrell, T. 2015 · 2015
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Imagenet large scale visual recognition challenge
Russakovsky, O.; Deng, J.; Su, H.; Krause, J.; Satheesh, S.; Ma, S.; Huang, Z.; Karpathy, A.; Khosla, A.; Bernstein, M.; et al. 2015 · 2015
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Very deep convolutional networks for large-scale image recognition
Simonyan, K.; and Zisserman, A. 2015 · 2015
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Label-embedding for image classification
Akata, Z.; Perronnin, F.; Harchaoui, Z.; and Schmid, C. 2016 · 2016
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Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Fasttext. zip: Compressing text classification models
Joulin, A.; Grave, E.; Bojanowski, P.; Douze, M.; Jégou, H.; and Mikolov, T. 2016 · 2016
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Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
Lin, D.; Dai, J.; Jia, J.; He, K.; and Sun, J. 2016 · 2016
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Matching networks for one shot learning
Vinyals, O.; Blundell, C.; Lillicrap, T.; Wierstra, D.; et al. 2016 · 2016
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Badrinarayanan, V.; Kendall, A.; and Cipolla, R. 2017 · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Finn, C.; Abbeel, P.; and Levine, S. 2017 · 2017
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Refinenet: Multi-path refinement networks for high-resolution semantic segmentation
Lin, G.; Milan, A.; Shen, C.; and Reid, I. 2017 · 2017
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Automatic differentiation in pytorch
Paszke, A.; Gross, S.; Chintala, S.; Chanan, G.; Yang, E.; DeVito, Z.; Lin, Z.; Desmaison, A.; Antiga, L.; and Lerer, A. 2017 · 2017
Advances in pre-training distributed word representations
Mikolov, T.; Grave, E.; Bojanowski, P.; Puhrsch, C.; and Joulin, A. 2018 · 2018
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Learning to compare: Relation network for few-shot learning
Sung, F.; Yang, Y.; Zhang, L.; Xiang, T.; Torr, P. H.; and Hospedales, T. M. 2018 · 2018
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Zero-shot recognition via semantic embeddings and knowledge graphs
Wang, X.; Ye, Y.; and Gupta, A. 2018 · 2018
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Meta-learning with differentiable closed-form solvers
Bertinetto, L.; Henriques, J. F.; Torr, P. H.; and Vedaldi, A. 2019 · 2019
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Attention-based multi-context guiding for few-shot semantic segmentation
Hu, T.; Yang, P.; Zhang, C.; Yu, G.; Mu, Y.; and Snoek, C. G. 2019 · 2019
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Adaptive masked weight imprinting for few-shot segmentation
Siam, M.; and Oreshkin, B. 2019 · 2019
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Optimization as a model for few-shot learning
Ravi, S.; and Larochelle, H. 2017 · 2017
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One-shot learning for semantic segmentation
Shaban, A.; Bansal, S.; Liu, Z.; Essa, I.; and Boots, B. 2017 · 2017
Cited alongside, same era.
Prototypical networks for few-shot learning
Snell, J.; Swersky, K.; and Zemel, R. 2017 · 2017
Cited alongside, same era.
A simple exponential family framework for zero-shot learning
Verma, V. K.; and Rai, P. 2017 · 2017
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Few-Shot Semantic Segmentation with Prototype Learning
Dong, N.; and Xing, E. P. 2018 · 2018
Cited alongside, same era.
Conditional networks for few-shot semantic segmentation
Rakelly, K.; Shelhamer, E.; Darrell, T.; Efros, A.; and Levine, S. 2018a
Cited in the paper.
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Panet: Few-shot image semantic segmentation with prototype alignment
Wang, K.; Liew, J. H.; Zou, Y.; Zhou, D.; and Feng, J. 2019 · 2019
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CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot Learning
Zhang, C.; Lin, G.; Liu, F.; Yao, R.; and Shen, C. 2019 · 2019
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Differentiable Meta-Learning Model for Few-Shot Semantic Segmentation
Tian, P.; Wu, Z.; Qi, L.; Wang, L.; Shi, Y.; and Gao, Y. 2020 · 2020
Closest in time.
Sg-one: Similarity guidance network for one-shot semantic segmentation
Zhang, X.; Wei, Y.; Yang, Y.; and Huang, T. S. 2020 · 2020
Closest in time.