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fashionXrecsys

Fashion Recommender Systems

The advent of online sites for the sale of fashion items and the consequent increase in users who benefit from them, has led in recent years to the development of more and more efficient recommendation systems for fashion. On this page, the articles related to this area have been and will be collected, divided into 3 tables based on their task:

  • item recommandation
  • outfit recommandation
  • other recommendation (size, attribute prediction, style consistency, etc.)

Papers

Item recommendation systems

Year Authors Title Venue Content Code Dataset
2021 Yu et al. Visually aware recommendation with aesthetic features VLDB Journal Temporal/item information Link
2020 Li et al. Bootstrapping Complete the Look at Pinterest SIGKDD Style Link
2020 Meichen et al. Design and realization of a collocation recommendation system for women's clothing Fangzhi Xuebao/Journal of Textile Research
2020 Dong et al. An interactive knowledge-based recommender system for fashion product design in the big data environment Information Sciences Item/body features
2019 Lu Sun et al. Personalized clothing recommendation combining user social circle and fashion style consistency CiHB U-I interaction, style
2018 Agarwal et al. Personalizing Similar Product Recommendations in Fashion E-commerce CORR User feedback Link
2018 Hwangbo et al. Recommendation system development for fashion retail e-commerce J.ECRA
2018 Zhou et al. Fashion Sensitive Clothing Recommendation Using Hierarchical Collocation Model ACM MM Deep visual features Link Link
2018 Jagadeesh et al. Large scale visual recommendations from street fashion images KDD Item features
2018 Qian et al. Algorithmic clothing: hybrid recommendation, from street-style-to-shop. CORR Item features
2017 Yin et al. Enhancing Fashion Recommendation with Visual Compatibility Relationship WWW U-I Interaction Link Link
2017 Zhao et al. Deep Style Match for Complementary Recommendation CORR Item features Link Link
2015 Bracher et al. Fashion DNA: Merging Content and Sales Data for Recommendation and Article Mapping CORR Item features Link
2015 Heintz et al. An LSTM-Based Dynamic Customer Model for Fashion Recommendation CEUR Item features Link
2015 Cheng Kang et al. Visually-Aware Fashion Recommendation and Design with Generative Image Models ICDM User feedback Link Link Link

Outfit recommendation systems

Year Authors Title Venue Content Code Dataset
2021 Zhan et al. A3-FKG: Attentive Attribute-Aware Fashion Knowledge Graph for Outfit Preference Prediction IEEE Transactions on Multimedia U-I Interaction
2020 Banerjee et al. BOXREC: Recommending a Box of Preferred Outfits in Online Shopping ACM Transactions on Intelligent Systems and Technology U-I features Link Link Link
2020 Li et al. Hierarchical Fashion Graph Network for Personalized Outfit Recommendation SIGIR
2020 Sridevi et al. Personalized fashion recommender system with image based neural networks IOP Conference Series: Materials Science and Engineering Deep visual feature
2020 Adewumi et al. A Unified Framework for Outfit Design and Advice Advances in Intelligent Systems and Computing Item-weather features
2020 Prato et al. Outfit completion and clothes recommendation CHI
2020 Tangseng et al. Toward Explainable Fashion Recommendation CVPR Item features
2019 Polania et al. Learning fashion compatibility across apparel categories for outfit recommendation ICIP Link
2018 Hu et al. Collaborative Fashion Recommendation: A Functional Tensor Factorization Approach ACM MM U-I interactions Link
2018 He et al. FashionNet: Personalized Outfit Recommendation with Deep Neural Network CORR Link
2018 McAuley et al. Image-Based Recommendations on Styles and Substitutes CORR Item features Link
2017 Jaradat Deep Cross-Domain Fashion Recommendation RecSys Social Network Link Link
2017 Yin et al. Improving Outfit Recommendation with Co-supervision of Fashion Generation WWW Deep visual features
2015 Lin et al. Explainable Fashion Recommendation with Joint Outfit Matching and Comment Generation TKDE Deep Visual Features
2014 Chen et al. POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion KDD Link

Other recommendation systems

Year Authors Title Venue Task Content Code Dataset
2021 Hidayati et al. Dress with Style: Learning Style from Joint Deep Embedding of Clothing Styles and Body Shapes IEEE Transactions on Multimedia Size Item style-Body features
2020 Wölbitsch et al. Mind the Gap: Exploring Shopping Preferences Across Fashion Retail Channels UMAP Shopping preferences
2020 Hao et al. ClothNet: A neural network based recommender system FSDM Ranking item Temporal/user information Link
2020 Brand et al. Paying the Pink Tax on a Blue Dress - Exploring Gender-Based Price-Premiums in Fashion Recommendations HCSE Gender-price Link
2019 He et al. Learning to Style-Aware Bayesian Personalized Ranking for Visual Recommendation J. IEEE ACCESS Style compatibility U-I interactions Link Link
2019 Yu Pan et al. Furniture style compatibility recommendation with cross-class triplet loss MTAP Style compatibility
2019 Yong Chung et al. Effect of facial makeup style recommendation on visual sensibility MTAP Facial makeup style
2018 Cardoso et al. Product Characterisation towards Personalisation: Learning Attributes from Unstructured Data to Recommend Fashion Products. KDD Attributes prediction Item features
2018 Kang et al. SVM and Collaborative Filtering-Based Prediction of User Preference for Digital Fashion Recommendation Systems T.IEICE User preferences predicitcion
2018 Liu et al. Learning Discrete Hashing Towards Efficient Fashion Recommendation JDS&E Attributes prediction Item features Link Link
2018 Zhang et al. Fashion Evaluation Method for Clothing Recommendation Based on Weak Appearance Feature JSP Size Weak appareance features
2017 Abdulla et al. Shop your Right Size: A System for Recommending Sizes for Fashion products WWW Size User features
2017 Guigourès et al. A hierarchical bayesian model for size recommendation in fashion RecSys Size

Authors:

Please contact the corresponing author Yashar Deldjoo for queries, comments and questions.

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