Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors

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Original

Fan Zhang, Guisheng Zhai, Meng Li, and Yizhao Liu · 2005

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One-shot learning of object categories

Fei-Fei Li, Rob Fergus, and Pietro Perona · 2006

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Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge J. Belongie · 2011

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Matching networks for one shot learning

Oriol Vinyals, Charles Blundell, Timothy P. Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016

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Jake Snell, Kevin Swersky, and Richard S. Zemel · 2017

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Hyperspherical variational auto-encoders

Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, and Jakub M. Tomczak · 2018

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Dynamic few-shot visual learning without forgetting

Spyros Gidaris and Nikos Komodakis · 2018

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Destruction and construction learning for fine-grained image recognition

Yuanfu Chen, Yalong Bai, Wei Zhang, and Tao Mei · 2019

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Poincaré maps for analyzing complex hierarchies in single-cell data

Anna Klimovskaia, David Lopez-Paz, Léon Bottou, and Maximilian Nickel · 2019

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Large scale learning of general visual representations for transfer

Original

Alexander I Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, and Neil Houlsby · 2019

Cited alongside, same era.

Meta-learning with differentiable convex optimization

Kwonjoon Lee, Subhransu Maji, Avinash Ravichandran, and Stefano Soatto · 2019

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Charting the right manifold: Manifold mixup for few-shot learning

Original

Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Vineeth N. Balasubramanian, and Balaji Krishnamurthy · 2019

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Continuous hierarchical representations with poincaré variational auto-encoders

Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, and Yee Whye Teh · 2019

Later among the works it cites.

Hyperspherical prototype networks

Pascal Mettes, Elise van der Pol, and Cees G. M. Snoek · 2019

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Generalizing from a few examples: A survey on few-shot learning

Yaqing Wang, Quanming Yao, James T. Kwok, and Lionel M. Ni · 2019

Later among the works it cites.