A Smart System for Selection of Optimal Product Images in E-Commerce

Chaudhuri, Anathbandhu; Messina, Paolo; Kokkula, Samrat; Subramanian, Aditya; Krishnan, Abhinandan; Gandhi, Shreyansh; Magnani, Alessandro; Kandaswamy, Venkatesh

doi:10.48550/arxiv.1811.07996

Cited by 1 publication

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“…The product listing image selection is largely done manually by professionals specializing in product listing adhering to Standard Operating Procdeures based on listing guidelines. Some prior published work [4] suggests solutions to build systems to solve image listing problems like de-duplication, image cropping etc.…”

Section: Catalogue Image Qualitymentioning

confidence: 99%

Unposed: Unsupervised Pose Estimation based Product Image Recommendations

Sharma,

Ahemad

2023

Preprint

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Product images are the most impressing medium of customer interaction on the product detail pages of e-commerce websites. Millions of products are onboarded on to webstore catalogues daily and maintaining a high quality bar for a product's set of images is a problem at scale. Grouping products by categories, clothing is a very high volume and high velocity category and thus deserves its own attention. Given the scale it is challenging to monitor the completeness of image set, which adequately details the product for the consumers, which in turn often leads to a poor customer experience and thus customer drop off.To supervise the quality and completeness of the images in the product pages for these product types and suggest improvements, we propose a Human Pose Detection based unsupervised method to scan the image set of a product for the missing ones. The unsupervised approach suggests a fair approach to sellers based on product and category irrespective of any biases. We first create a reference image set of popular products with wholesome imageset. Then we create clusters of images to label most desirable poses to form the classes for the reference set from these ideal products set. Further, for all test products we scan the images for all desired pose

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Section: Catalogue Image Qualitymentioning

confidence: 99%