  We propose a visually conditioned music remixing system by incorporating deep
visual and audio models. The method is based on a state of the art audio-visual
source separation model which performs music instrument source separation with
video information. We modified the model to work with user-selected images
instead of videos as visual input during inference to enable separation of
audio-only content. Furthermore, we propose a remixing engine that generalizes
the task of source separation into music remixing. The proposed method is able
to achieve improved audio quality compared to remixing performed by the
separate-and-add method with a state-of-the-art audio-visual source separation
model.
