Fashion Outfit Generation for E-commerce

@inproceedings{Bettaney2019FashionOG,
  title={Fashion Outfit Generation for E-commerce},
  author={Elaine M. Bettaney and Stephen R. Hardwick and Odysseas Zisimopoulos and B. Chamberlain},
  booktitle={eCOM@SIGIR},
  year={2019}
}
Combining items of clothing into an outfit is a major task in fashion retail. [...] Key Method We use a multilayer neural network fed by visual and textual features to learn embeddings of items in a latent style space such that compatible items of different types are embedded close to one another. We train our model using the ASOS outfits dataset, which consists of a large number of outfits created by professional stylists and which we release to the research community. Our model shows strong performance in an…Expand

References

SHOWING 1-10 OF 26 REFERENCES
Learning Type-Aware Embeddings for Fashion Compatibility
Learning Fashion Compatibility with Bidirectional LSTMs
Recommending Outfits from Personal Closet
FashionNet: Personalized Outfit Recommendation with Deep Neural Network
Mining Fashion Outfit Composition Using an End-to-End Deep Learning Approach on Set Data
Outfit Generation and Style Extraction via Bidirectional LSTM and Autoencoder
Compatibility Family Learning for Item Recommendation and Generation
Learning Visual Clothing Style with Heterogeneous Dyadic Co-Occurrences
Collaborative Fashion Recommendation: A Functional Tensor Factorization Approach
Image-Based Recommendations on Styles and Substitutes
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