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Complete the Look: Scene-based Complementary Product Recommendation. Modeling fashion compatibility is challenging due to its complexity and subjectivity. Existing work focuses on predicting compatibility between product images (e.g. an image containing a t-shirt and an image containing a pair of jeans).


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"Complete the Look" is a style-focused concept where the goal is to help users put together an entire outfit, instead of just picking out a single piece of clothing. This can be a challenging.


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How to recommend products that match a given scene image? This is the challenge of 'Complete the Look', a novel task proposed by Stanford Computer Science researchers. They introduce a method to learn the scene-product compatibility from fashion or interior design images, using CNNs and attention mechanisms. Read their paper to find out more.


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For online shoppers, complete the look: Enhances the online shopping experience of your store; Builds trust and positions you as the fashion or design expert—your visitors will value your expert styling advice; Helps shoppers to visualize the product and how it might look with other branded items. While the most sophisticated ecommerce.


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Complete the Look takes context like an outfit, body type, season, indoors vs. outdoors, various pieces of furniture, and the overall aesthetics of a room, to power taste-based recommendations.


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Vintage Charm Curated Collection. Lush Decor takes the time and guesswork out of achieving a decorator-inspired, just-right look for the home with Complete the Look - a one-stop shopping, curated concept. Complete the Look leverages Lush Decor's vast and versatile product line to recommend visually compatible designs for a pulled-together look.


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"Complete the look" recommendations resembles an experienced and well-trained seller in a high-end physical store, who would recommend additional items to style each full space. "Complete the look" helps customers visualize how they can combine each item with additional purchases, or even with their own current furniture..


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In this work, we propose a new task called `Complete the Look', which seeks to recommend visually compatible products based on scene images. We design an approach to extract training data for this task, and propose a novel way to learn the scene-product compatibility from fashion or interior design images. Our approach measures compatibility.


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Why Complete the Look Matters for Ecommerce. Online communication is increasingly driven by images. Instagram Stories has 300 million daily active users, to cite just one photo-focused statistic.


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The Pinterest Complete the Look dataset consists of over 1 million outfits and 4 million objects. It can be used to predict style compatibility between fashion items in order to recommend complementary items that complete an outfit.


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In a highly competitive ecommerce market "complete the look recommendations" feature can make fashion e-shops stand out. According to a recent study by Statista, worldwide retail ecommerce sales will reach a new high by the end of 2021 and will account for 17.5% of the total global retail sales.. This means that all ecommerce businesses will have to find new, innovative ways to establish.


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How can we recommend complementary products to customers based on the scene they are in? This paper proposes a novel method that leverages visual and textual features to model fashion compatibility and generate personalized suggestions. Read the full paper to learn more about the complete the look problem and the proposed solution.


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Complete the Look: Scene-based Complementary Product Recommendation Wang-Cheng Kang†⇤, Eric Kim‡, Jure Leskovec‡§, Charles Rosenberg‡, Julian McAuley† ‡Pinterest, §Stanford University, †UC San Diego {wckang,jmcauley}@ucsd.edu, {erickim,jure,crosenberg}@pinterest.com Abstract Modeling fashion compatibility is challenging due to its