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ENHANCING PRODUCT IMAGES FOR CLICK-THROUGH RATE IMPROVEMENT

Citation Author(s):
Yeongnam Chae, Mitsuru, Bjorn Stenger
Submitted by:
Yeongnam Chae
Last updated:
4 October 2018 - 9:03pm
Document Type:
Poster
Document Year:
2018
Event:
Presenters Name:
Mitsuru Nakazawa
Paper Code:
2578

Abstract 

Abstract: 

This paper proposes a statistical method to enhance image quality in order to increase the click-through rate (CTR) of product images. We build a joint probability model of global image features for photos of different product categories. The images are modified in terms of brightness, contrast, and sharpness in order to increase the expected CTR. The effectiveness of the method is evaluated using a perceptual user study, comparing it to histogram equalization methods, and by conducting an A/B test over one week on the e-commerce site Rakuten Ichiba.

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Dataset Files

Poster_ICIP2018_fix.pdf

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