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An Application to Generate Style Guided Compatible Outfit

arXiv 2205.00663 ↗First posted 2 May 2022cs.IR cs.CVcited by 0

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Abstract (arXiv)

Fashion recommendation has witnessed a phenomenal growth of research, particularly in the domains of shop-the-look, contextaware outfit creation, personalizing outfit creation etc. Majority of the work in this area focuses on better understanding of the notion of complimentary relationship between lifestyle items. Quite recently, some works have realised that style plays a vital role in fashion, especially in the understanding of compatibility learning and outfit creation. In this paper, we would like to present the end-to-end design of a methodology in which we aim to generate outfits guided by styles or themes using a novel style encoder network. We present an extensive analysis of different aspects of our method through various experiments. We also provide a demonstration api to showcase the ability of our work in generating outfits based on an anchor item and styles.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 22 references that are in the map. First posted on arXiv 2 May 2022.

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13 of 22 references.

References · 13

  1. 2016Variational Inference: A Review for Statisticianscited by 1,466
  2. 2015Image-based Recommendations on Styles and Substitutescited by 702
  3. 2021Dive into Deep Learningcited by 111
  4. 2017Learning Fashion Compatibility with Bidirectional LSTMscited by 69
  5. 2019POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashioncited by 63
  6. 2018Learning Type-Aware Embeddings for Fashion Compatibilitycited by 61
  7. 2019Fashion Outfit Complementary Item Retrievalcited by 42
  8. 2018Outfit Generation and Style Extraction via Bidirectional LSTM and Autoencodercited by 9
  9. 2020Learning the Compositional Visual Coherence for Complementary Recommendationscited by 9
  10. 2019Coherent and Controllable Outfit Generationcited by 8
  11. 2019Fashion Outfit Generation for E-commercecited by 6
  12. 2019Supporting stylists by recommending fashion stylecited by 6
1 more
  1. 2019Theme-Matters: Fashion Compatibility Learning via Theme Attentioncited by 4

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