# Dress Well via Fashion Cognitive Learning

arXiv: https://arxiv.org/abs/2208.00639 · HTML: https://mlsanity.com/paper/2208.00639/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 31 references that are in the map.
- First posted on arXiv 1 Aug 2022.

## Builds on (most cited first, 18 of 18)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Multi-Label Image Recognition with Graph Convolutional Networks](https://mlsanity.com/paper/1904.03582/) (2019)
- [CNN-RNN: A Unified Framework for Multi-label Image Classification](https://mlsanity.com/paper/1604.04573/) (2016)
- [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)
- [Fashion Outfit Complementary Item Retrieval](https://mlsanity.com/paper/1912.08967/) (2019)
- [Hierarchical Fashion Graph Network for Personalized Outfit Recommendation](https://mlsanity.com/paper/2005.12566/) (2020)
- [Outfit Generation and Style Extraction via Bidirectional LSTM and Autoencoder](https://mlsanity.com/paper/1807.03133/) (2018)
- [Outfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network](https://mlsanity.com/paper/1907.11496/) (2019)
- [Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach](https://mlsanity.com/paper/2005.12439/) (2020)
- [Learning Color Compatibility in Fashion Outfits](https://mlsanity.com/paper/2007.02388/) (2020)
- [PAI-BPR: Personalized Outfit Recommendation Scheme with Attribute-wise Interpretability](https://mlsanity.com/paper/2008.01780/) (2020)
- [Visually-Aware Personalized Recommendation using Interpretable Image Representations](https://mlsanity.com/paper/1806.09820/) (2018)
- [Regularizing Reasons for Outfit Evaluation with Gradient Penalty](https://mlsanity.com/paper/2002.00460/) (2020)
- [False Negative Distillation and Contrastive Learning for Personalized Outfit Recommendation](https://mlsanity.com/paper/2110.06483/) (2021)

## Abstract (arXiv)

Fashion compatibility models enable online retailers to easily obtain a large number of outfit compositions with good quality. However, effective fashion recommendation demands precise service for each customer with a deeper cognition of fashion. In this paper, we conduct the first study on fashion cognitive learning, which is fashion recommendations conditioned on personal physical information. To this end, we propose a Fashion Cognitive Network (FCN) to learn the relationships among visual-semantic embedding of outfit composition and appearance features of individuals. FCN contains two submodules, namely outfit encoder and Multi-label Graph Neural Network (ML-GCN). The outfit encoder uses a convolutional layer to encode an outfit into an outfit embedding. The latter module learns label classifiers via stacked GCN. We conducted extensive experiments on the newly collected O4U dataset, and the results provide strong qualitative and quantitative evidence that our framework outperforms alternative methods.