English

Scaling Cross-Domain Content-Based Image Retrieval for E-commerce Snap and Search Application

Information Retrieval 2022-04-27 v1 Computer Vision and Pattern Recognition

Abstract

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.

Cite

@article{arxiv.2204.11593,
  title  = {Scaling Cross-Domain Content-Based Image Retrieval for E-commerce Snap and Search Application},
  author = {Isaac Kwan Yin Chung and Minh Tran and Eran Nussinovitch},
  journal= {arXiv preprint arXiv:2204.11593},
  year   = {2022}
}

Comments

ECIR 2022 Industry Day

R2 v1 2026-06-24T10:57:40.759Z