Multi-label Movie Genre Detection from a Movie Poster Using Knowledge Transfer Learning

Abstract

The task of predicting a movie genre from its poster can be very challenging owing to the high variability of movie posters. A novel approach for the generation of a multi-label movie genre prediction from its poster using neural networks that employ knowledge transfer learning has been proposed in this paper. This approach works on two fronts; one is aimed at creating a large, diverse and balanced dataset for movie genre prediction. The second front involves reframing the problem to simpler single-label multi-class classification and generating a multi-label multi-class prediction on a given movie poster as input. The experimental evaluation suggests that our approach generates a remarkable accuracy which is a result of a larger, evenly distributed dataset, simplifying the problem to a single-label multi-class classification problem and because of the use of knowledge transfer learning to extract higher-level feature.