论文标题
使用多尺度CNN的图像检索
Image Retrieval using Multi-scale CNN Features Pooling
论文作者
论文摘要
在本文中，我们通过基于卷积神经网络的激活来学习图像表示来解决图像检索的问题。我们提出了一个端到端的可训练网络体系结构，该架构利用基于NetVlad的新型多尺度本地合并和基于样品的三重态挖掘程序，难以获得有效的图像表示。广泛的实验表明，我们的方法能够在三个标准数据集上达到最新结果。
In this paper, we address the problem of image retrieval by learning images representation based on the activations of a Convolutional Neural Network. We present an end-to-end trainable network architecture that exploits a novel multi-scale local pooling based on NetVLAD and a triplet mining procedure based on samples difficulty to obtain an effective image representation. Extensive experiments show that our approach is able to reach state-of-the-art results on three standard datasets.
