Deep Metric Learning via Adaptive Learnable Assessment

CVPR 2020 Wenzhao Zheng Jiwen Lu Jie Zhou

In this paper, we propose a deep metric learning via adaptive learnable assessment (DML-ALA) method for image retrieval and clustering, which aims to learn a sample assessment strategy to maximize the generalization of the trained metric. Unlike existing deep metric learning methods that usually utilize a fixed sampling strategy like hard negative mining, we propose a sequence-aware learnable assessor which re-weights each training example to train the metric towards good generalization... (read more)

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