Visual Search at Pinterest

Yushi Jing, David C. Liu, Dmitry Kislyuk, Andrew Zhai, Jiajing Xu, Jeff Donahue, Sarah Tavel

Abstract: We demonstrate that, with the availability of distributed computation platforms such as Amazon Web Services and open-source tools, it is possible for a small engineering team to build, launch and maintain a cost-effective, large-scale visual search system. We also demonstrate, through a comprehensive set of live experiments at Pinterest, that content recommendation powered by visual search improves user engagement. By sharing our implementation details and learnings from launching a commercial visual search engine from scratch, we hope visual search becomes more widely incorporated into today's commercial applications.