Learning Image Memorability with Feedback-Based Training

Abstract

Memorability, or the likelihood that an image is later remembered, is an intrinsic stimulus property that is remarkably consistent across viewers. Despite this consistency in what people remember and forget, previous findings suggest a lack of consistency in what individuals subjectively believe to be memorable and forgettable. We aimed to improve the ability of participants to judge memorability using a feedback-based training paradigm containing face images (Experiment 1) or scene images (Experiment 2 and its replication and control experiments). Overall, participants were fairly accurate at categorizing the memorability of images. In response to the training, participants were able to improve their memorability judgments of scenes, but not faces. Those who used certain strategies to perform the task, namely relying on characteristic features of the scenes, showed greater learning. Although participants improved slightly over time, they never reached the level of ResMem, the leading DNN for estimating image memorability. These results suggest that with training, human participants can better their understanding of image memorability, but may be unable to access its full variance.