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

Gwangjin LeeWon JoYukyung Choi
Published in: Sensors (Basel, Switzerland) (2023)
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.
Keyphrases
  • deep learning
  • convolutional neural network