Traditional methods on sketch based image retrieval leveraged edge detection algorithms to turn natu-ral images into edge maps, but it can not well decrease the visual diversity between natural images and sketches. For this problem, we propose a novel sketch based image retrieval method based on conditional generative ad-versarial networks. Our method is demonstrated as follows: Firstly, we train the conditional generative adversarial networks, of which the generative network is constituted by an edges-to-photo mapping network; secondly, sketch images are converted to natural images by the generative network; thirdly, we use deep convolution neural net-work to extract the deep feature to achieve retrieval. Experiments on retrieval show positive results.%传统的手绘图像检索方法将自然图像通过边缘检测算法转换成"类手绘图",不能很好地减小自然图像与手绘图像之间的视觉差异.针对此问题,提出一种基于条件生成对抗网络的手绘图像检索方法.首先训练条件生成对抗网络,其中生成器由边缘图至自然图像的映射网络构成;然后通过生成器将手绘图转换为自然图像,以消除二者的视觉差异;最后使用深度卷积神经网络提取深度特征进行相似度度量,达到检索的目的.在基准数据库上进行实验的结果显示,该方法的检索精度有明显提高.
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