  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.
