Multimodality and Deep Learning when predicting Media



Multimodality and Deep Learning when predicting Media

Multimodality and Deep Learning when predicting Media
Research Paper / MediaEval Workshop / Sep 2017 / Machine/Deep Learning/AI, Computer Vision

This paper summarizes the computational models that Technicolor proposes to predict interestingness of images and videos within the MediaEval 2017 PredictingMedia Interestingness Task. Our systems are based on deep learning architectures and exploit the use of both semantic and multimodal features. Based on the obtained results, we discuss our findings and obtain some scientific perspectives for the task.