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Show and Recall @ MediaEval 2018 ViMemNet: Predicting Video Memorability

MediaEval 2018

Published November 23, 2018

Ritwick Chaudhry, Manoj Kilaru, Sumit Shekhar

In the current age of expanding access to the Internet, there has been a flood of videos on the web. Studying the human cognitive factors that affect the consumption of these videos is becoming increasingly important, to be able to effectively organize and curate them. One such important cognitive factor is Video Memorability, which is the ability to recall a video’s content after watching it. In this paper, we present our approach to solving the MediaEval 2018 Predicting Media Memorability Task. We develop a 3-forked pipeline for predicting Memorability Scores, which leverages the visual image features (both low-level and high-level), the image saliency in different video frames, and the information present in the captions. We also explore the relevance of other features such as image memorability scores of the different frames in the video, and present a detailed analysis of the results.

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