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

Autor:	Chung, Isaac Kwan Yin, Tran, Minh, Nussinovitch, Eran
Rok vydání:	2022
Předmět:	Computer Science - Information Retrieval Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	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. Comment: ECIR 2022 Industry Day
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2204.11593 Zobrazit plný text záznamu View this record from Arxiv