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VERD: Emergence of Product-Based Video E-Commerce Retrieval Dataset from User's Perspective.
Lee, Gwangjin; Jo, Won; Choi, Yukyung.
Afiliação
  • Lee G; Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Republic of Korea.
  • Jo W; Department of Artificial Intelligence, Sejong University, Seoul 05006, Republic of Korea.
  • Choi Y; Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Republic of Korea.
Sensors (Basel) ; 23(1)2023 Jan 03.
Article em En | MEDLINE | ID: mdl-36617111
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Armazenamento e Recuperação da Informação / Comércio Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Armazenamento e Recuperação da Informação / Comércio Idioma: En Ano de publicação: 2023 Tipo de documento: Article