  Image perception is one of the most direct ways to provide contextual
information about a user concerning his/her surrounding environment; hence
images are a suitable proxy for contextual recommendation. We propose a novel
representation learning framework for image-based music recommendation that
bridges the heterogeneity gap between music and image data; the proposed method
is a key component for various contextual recommendation tasks. Preliminary
experiments show that for an image-to-song retrieval task, the proposed method
retrieves relevant or conceptually similar songs for input images.
