VERD: Emergence of Product-Based Video E-Commerce Retrieval Dataset from User's Perspective

Customer demands for product search are growing as a result of the recent growth of the e-commerce market. According to this trend, studies on object-centric retrieval using product images have emerged, but it is difficult to respond to complex user-environment scenarios and a search requires a vast amount of data. In this paper, we propose the Video E-commerce Retrieval Dataset (VERD), which utilizes user-perspective videos. In addition, a benchmark and additional experiments are presented to demonstrate the need for independent research on product-centered video-based retrieval. VERD is publicly accessible for academic research and can be downloaded by contacting the author by email.

Automated summary

Customer demands for product search are increasing due to the growth of e-commerce market. Existing studies focus on object-centric retrieval using product images, but responding to complex user-environment scenarios and handling large amounts of data remains challenging. This paper introduces the Video E-commerce Retrieval Dataset (VERD) that utilizes user-perspective videos, and presents a benchmark and additional experiments to highlight the need for independent research on product-centered video-based retrieval. VERD is available for academic research and can be downloaded by contacting the author via email.