Fashion Focus: Multi-modal Retrieval System for Video Commodity Localization in E-commerce

Nowadays, live-stream and short video shopping in E-commerce have grown exponentially. However, the sellers are required to manually match images of selling products timestamp exhibition untrimmed video, resulting a complicated process. To solve problem, we present an innovative demonstration multi-modal retrieval system called ``Fashion Focus'', which enables exactly localize product online as focuses. Different modality contributes community localization, including visual content, linguistic features interaction context jointly investigated via presented learning. Our employs two procedures for analysis, content structuring retrieval, automatically achieve accurate video-to-shop matching. Fashion Focus presents unified framework that can orientate consumers towards relevant exhibitions during watching videos help effectively deliver over search recommendation.