CVAIDec 4, 2021

An Annotated Video Dataset for Computing Video Memorability

arXiv:2112.02303v112 citations
Originality Synthesis-oriented
AI Analysis

This provides a resource for researchers studying video memorability, but it is incremental as it builds on existing annotation methods.

The authors created a dataset of short videos annotated for memorability by 1,275 users, measuring recall over short and long terms with reaction times, and used it in a 2020 benchmark.

Using a collection of publicly available links to short form video clips of an average of 6 seconds duration each, 1,275 users manually annotated each video multiple times to indicate both long-term and short-term memorability of the videos. The annotations were gathered as part of an online memory game and measured a participant's ability to recall having seen the video previously when shown a collection of videos. The recognition tasks were performed on videos seen within the previous few minutes for short-term memorability and within the previous 24 to 72 hours for long-term memorability. Data includes the reaction times for each recognition of each video. Associated with each video are text descriptions (captions) as well as a collection of image-level features applied to 3 frames extracted from each video (start, middle and end). Video-level features are also provided. The dataset was used in the Video Memorability task as part of the MediaEval benchmark in 2020.

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