# An Application to Generate Style Guided Compatible Outfit

arXiv: https://arxiv.org/abs/2205.00663 · HTML: https://mlsanity.com/paper/2205.00663/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 22 references that are in the map.
- First posted on arXiv 2 May 2022.

## Builds on (most cited first, 13 of 13)

- [Variational Inference: A Review for Statisticians](https://mlsanity.com/paper/1601.00670/) (2016)
- [Image-based Recommendations on Styles and Substitutes](https://mlsanity.com/paper/1506.04757/) (2015)
- [Dive into Deep Learning](https://mlsanity.com/paper/2106.11342/) (2021)
- [Learning Fashion Compatibility with Bidirectional LSTMs](https://mlsanity.com/paper/1707.05691/) (2017)
- [POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion](https://mlsanity.com/paper/1905.01866/) (2019)
- [Learning Type-Aware Embeddings for Fashion Compatibility](https://mlsanity.com/paper/1803.09196/) (2018)
- [Fashion Outfit Complementary Item Retrieval](https://mlsanity.com/paper/1912.08967/) (2019)
- [Outfit Generation and Style Extraction via Bidirectional LSTM and Autoencoder](https://mlsanity.com/paper/1807.03133/) (2018)
- [Learning the Compositional Visual Coherence for Complementary Recommendations](https://mlsanity.com/paper/2006.04380/) (2020)
- [Coherent and Controllable Outfit Generation](https://mlsanity.com/paper/1906.07273/) (2019)
- [Fashion Outfit Generation for E-commerce](https://mlsanity.com/paper/1904.00741/) (2019)
- [Supporting stylists by recommending fashion style](https://mlsanity.com/paper/1908.09493/) (2019)
- [Theme-Matters: Fashion Compatibility Learning via Theme Attention](https://mlsanity.com/paper/1912.06227/) (2019)

## 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.