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arXiv:1802.04914cs.CV

Web-Scale Responsive Visual Search at Bing

Houdong Hu, Yan Wang, Linjun Yang, Pavel Komlev, Li Huang, Xi Chen, Jiapei Huang, Ye Wu, Meenaz Merchant, Arun Sacheti

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Abstract

In this paper, we introduce a web-scale general visual search system deployed in Microsoft Bing. The system accommodates tens of billions of images in the index, with thousands of features for each image, and can respond in less than 200 ms. In order to overcome the challenges in relevance, latency, and scalability in such large scale of data, we employ a cascaded learning-to-rank framework based on various latest deep learning visual features, and deploy in a distributed heterogeneous computing platform. Quantitative and qualitative experiments show that our system is able to support various applications on Bing website and apps.

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Journal reference
DOI
Subjects
cs.CVComputer Vision and Pattern Recognition

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  1. Using Vectorize to build an unreasonably good search engine in 160 lines of code 1 comment

    • I've not heard about Bing using vector search, at least outside of their image search feature https://arxiv.org/abs/1802.04914 Information about how Bing text search works appears to be pretty sparse though. One of the great mysteries to me right now is how ChatGPT search…

      simonwView on HNParent context

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