  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.

Computer Vision and Pattern Recognition;Human-Computer Interaction