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Conventional detection networks usually need abundant labeled training samples, while humans can learn new concepts incrementally with just a few examples.
Catastrophic interference in connectionist networks: The sequential learning problem
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Repmet: Representative-based metric learning for classification and few-shot object detection
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Juan-Manuel Perez-Rua, Xiatian Zhu, Timothy M Hospedales, and Tao Xiang · 2020
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Few-shot class-incremental learning
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Frustratingly simple few-shot object detection
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Few-shot object detection and viewpoint estimation for objects in the wild
Yang Xiao and Renaud Marlet · 2020
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