DeepAI AI Chat
Log In Sign Up

FashionNet: Personalized Outfit Recommendation with Deep Neural Network

by   Tong He, et al.
University of Electronic Science and Technology of China

With the rapid growth of fashion-focused social networks and online shopping, intelligent fashion recommendation is now in great need. We design algorithms which automatically suggest users outfits (e.g. a shirt, together with a skirt and a pair of high-heel shoes), that fit their personal fashion preferences. Recommending sets, each of which is composed of multiple interacted items, is relatively new to recommender systems, which usually recommend individual items to users. We explore the use of deep networks for this challenging task. Our system, dubbed FashionNet, consists of two components, a feature network for feature extraction and a matching network for compatibility computation. The former is achieved through a deep convolutional network. And for the latter, we adopt a multi-layer fully-connected network structure. We design and compare three alternative architectures for FashionNet. To achieve personalized recommendation, we develop a two-stage training strategy, which uses the fine-tuning technique to transfer a general compatibility model to a model that embeds personal preference. Experiments on a large scale data set collected from a popular fashion-focused social network validate the effectiveness of the proposed networks.


page 2

page 8


SocialTrans: A Deep Sequential Model with Social Information for Web-Scale Recommendation Systems

On social network platforms, a user's behavior is based on his/her perso...

Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach

With the growth of online shopping for fashion products, accurate fashio...

Recommending Outfits from Personal Closet

We consider grading a fashion outfit for recommendation, where we assume...

Learning fashion compatibility across apparel categories for outfit recommendation

This paper addresses the problem of generating recommendations for compl...

Deep Set-to-Set Matching and Learning

Matching two sets of items, called set-to-set matching problem, is being...

An LSTM-Based Dynamic Customer Model for Fashion Recommendation

Online fashion sales present a challenging use case for personalized rec...

Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification

Recent years have witnessed the increasing popularity of Location-based ...