1 research outputs found
Buy Me That Look: An Approach for Recommending Similar Fashion Products
Have you ever looked at an Instagram model, or a model in a fashion
e-commerce web-page, and thought \textit{"Wish I could get a list of fashion
items similar to the ones worn by the model!"}. This is what we address in this
paper, where we propose a novel computer vision based technique called
\textbf{ShopLook} to address the challenging problem of recommending similar
fashion products. The proposed method has been evaluated at Myntra
(www.myntra.com), a leading online fashion e-commerce platform. In particular,
given a user query and the corresponding Product Display Page (PDP) against the
query, the goal of our method is to recommend similar fashion products
corresponding to the entire set of fashion articles worn by a model in the PDP
full-shot image (the one showing the entire model from head to toe). The
novelty and strength of our method lies in its capability to recommend similar
articles for all the fashion items worn by the model, in addition to the
primary article corresponding to the query. This is not only important to
promote cross-sells for boosting revenue, but also for improving customer
experience and engagement. In addition, our approach is also capable of
recommending similar products for User Generated Content (UGC), eg., fashion
article images uploaded by users. Formally, our proposed method consists of the
following components (in the same order): i) Human keypoint detection, ii) Pose
classification, iii) Article localisation and object detection, along with
active learning feedback, and iv) Triplet network based image embedding model.Comment: Accepted at the IEEE International Conference on Multimedia
Information Processing and Retrieval (MIPR) 202