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Found 9 papers, 3 papers with code
Overview of The MediaEval 2022 Predicting Video Memorability Task
This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022.
Experiences from the MediaEval Predicting Media Memorability Task
The Predicting Media Memorability task in the MediaEval evaluation campaign has been running annually since 2018 and several different tasks and data sets have been used in this time.
Deepfake Caricatures: Amplifying attention to artifacts increases deepfake detection by humans and machines
Second, they allow us to generate novel "Deepfake Caricatures": transformations of the deepfake that exacerbate artifacts to improve human detection.
Overview of The MediaEval 2021 Predicting Media Memorability Task
This paper describes the MediaEval 2021 Predicting Media Memorability}task, which is in its 4th edition this year, as the prediction of short-term and long-term video memorability remains a challenging task.
VA-RED$^2$: Video Adaptive Redundancy Reduction
An inherent property of real-world videos is the high correlation of information across frames which can translate into redundancy in either temporal or spatial feature maps of the models, or both.
Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability
Based on our findings we propose a new mathematical formulation of memorability decay, resulting in a model that is able to produce the first quantitative estimation of how a video decays in memory over time.
We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos
This allows our model to perform cognitive tasks such as set abstraction (which general concept is in common among a set of videos?
Predicting Visual Importance Across Graphic Design Types
This paper introduces a Unified Model of Saliency and Importance (UMSI), which learns to predict visual importance in input graphic designs, and saliency in natural images, along with a new dataset and applications.
How Much Time Do You Have? Modeling Multi-Duration Saliency
What jumps out in a single glance of an image is different than what you might notice after closer inspection.
