Attention-based Fusion for Outfit Recommendation

TL;DR

This paper introduces an attention-based fusion approach that combines product images and descriptions to enhance outfit recommendation accuracy, demonstrating superior performance on benchmark datasets.

Contribution

It proposes a novel attention-based fusion method for outfit recommendation that effectively integrates visual and textual information for better item understanding.

Findings

Outperforms state-of-the-art on three datasets

Attention fusion improves feature representation

Effective integration of image and description data

Abstract

This paper describes an attention-based fusion method for outfit recommendation which fuses the information in the product image and description to capture the most important, fine-grained product features into the item representation. We experiment with different kinds of attention mechanisms and demonstrate that the attention-based fusion improves item understanding. We outperform state-of-the-art outfit recommendation results on three benchmark datasets.