# Analyzing Images for Music Recommendation

Source: [Analyzing Images for Music Recommendation](<https://www.sota2.com/research/paper/68fa69f41e209131cea253de>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:13:37.567Z

Authors: Anant Baijal, Vivek Agarwal, Danny Hyun

Published: 2021-05-15T04:14:47.000Z

## Abstract

Experiencing images with suitable music can greatly enrich the overall user experience. The proposed image analysis method treats an artwork image differently from a photograph image. Automatic image classification is performed using deep-learning based models. An illustrative analysis showcasing the ability of our deep-models to inherently learn and utilize perceptually relevant features when classifying artworks is also presented. The Mean Opinion Score (MOS) obtained from subjective assessments of the respective image and recommended music pairs supports the effectiveness of our approach.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2105.07135>)

[PDF](<https://arxiv.org/pdf/2105.07135.pdf>)