论文标题
用于电子商务快照和搜索应用程序的基于跨域内容的图像检索
Scaling Cross-Domain Content-Based Image Retrieval for E-commerce Snap and Search Application
论文作者
论文摘要
在ECIR 2022年的行业演讲中，我们说明了如何使用级联方法和视觉搜索和分类功能的结合来应对大规模跨域内容检索的主要挑战。具体来说，我们提出了一个能够处理电子商务使用情况的数据规模以及查询和画廊图像池的跨域性质。我们展示了现实世界电子商务快照和搜索用例中应用的方法及其对排名和延迟性能的影响。
In this industry talk at ECIR 2022, we illustrate how we approach the main challenges from large scale cross-domain content-based image retrieval using a cascade method and a combination of our visual search and classification capabilities. Specifically, we present a system that is able to handle the scale of the data for e-commerce usage and the cross-domain nature of the query and gallery image pools. We showcase the approach applied in real-world e-commerce snap and search use case and its impact on ranking and latency performance.
