Object memorability prediction is a task of estimating the probability that a human recognises the recurrence of an object after a single view. Initial research on object memorability showed that it is possible to predict the object memorability scores from the intrinsic features of an object. Though the existing works proposed some of the features for object memorability prediction task, the influence of Spatial-location and Spatial-size of an object to its memorability have not been explored yet. In this work, the importance of these two characteristics in determining object memorability prediction is investigated and the same is demonstrated by building a baseline model. Further, a deep learning model is devised for automatic feature learning on these two object characteristics. Experimental results highlight that the Spatial-location and Spatial-size of an object play a significant role in object memorability prediction and the proposed models outperformed the existing methods. (C) 2019 Elsevier Inc. All rights reserved.
