Generative Outpainting To Enhance the Memorability of Short-Form Videos
Alan Byju, Aman Sudhindra Ladwa, Lorin Sweeney, Alan F., Smeaton

TL;DR
This paper explores how generative outpainting can be used to expand short-form videos and improve their memorability, leveraging deep learning models and saliency-based evaluation.
Contribution
It introduces a novel application of generative outpainting to enhance video memorability and identifies the most effective model and saliency-based methods for this purpose.
Findings
Outpainting improves video memorability scores.
Saliency-based outpainting outperforms other methods.
Optimal model identified for enhancing short-form videos.
Abstract
With the expanding use of the short-form video format in advertising, social media, entertainment, education and more, there is a need for such media to both captivate and be remembered. Video memorability indicates to us how likely a video is to be remembered by a viewer who has no emotional or personal connection with its content. This paper presents the results of using generative outpainting to expand the screen size of a short-form video with a view to improving its memorability. Advances in machine learning and deep learning are compared and leveraged to understand how extending the borders of video screensizes can affect their memorability to viewers. Using quantitative evaluation we determine the best-performing model for outpainting and the impact of outpainting based on image saliency on video memorability scores
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputer Graphics and Visualization Techniques · Generative Adversarial Networks and Image Synthesis · Advanced Vision and Imaging
