Visual interest & affect prediction is a very interesting area of research in the area of computer vision. In this paper, we propose a transfer learning and attention mechanism based neural network model to predict visual interest & affective dimensions in digital photos. Learning the multi-dimensional affects is addressed through a multi-task learning framework. With various experiments we show the effectiveness of the proposed approach. Evaluation of our model on the benchmark dataset shows large improvement over current state-of-the-art systems.
@article{arxiv.2005.12770,
title = {Visual Interest Prediction with Attentive Multi-Task Transfer Learning},
author = {Deepanway Ghosal and Maheshkumar H. Kolekar},
journal= {arXiv preprint arXiv:2005.12770},
year = {2020}
}