Search Results for author: Camilo Fosco

Found 9 papers, 3 papers with code

Experiences from the MediaEval Predicting Media Memorability Task

no code implementations7 Dec 2022 Alba García Deco de Herrera, Mihai Gabriel Constantin, Chaire-Hélène Demarty, Camilo Fosco, Sebastian Halder, Graham Healy, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Mushfika Sultana, Lorin Sweeney

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

no code implementations1 Jun 2022 Camilo Fosco, Emilie Josephs, Alex Andonian, Allen Lee, Xi Wang, Aude Oliva

Second, they allow us to generate novel "Deepfake Caricatures": transformations of the deepfake that exacerbate artifacts to improve human detection.

DeepFake Detection Face Swapping +2

Overview of The MediaEval 2021 Predicting Media Memorability Task

no code implementations11 Dec 2021 Rukiye Savran Kiziltepe, Mihai Gabriel Constantin, Claire-Helene Demarty, Graham Healy, Camilo Fosco, Alba Garcia Seco de Herrera, Sebastian Halder, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Lorin Sweeney

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.

EEG Electroencephalogram (EEG)

VA-RED$^2$: Video Adaptive Redundancy Reduction

no code implementations ICLR 2021 Bowen Pan, Rameswar Panda, Camilo Fosco, Chung-Ching Lin, Alex Andonian, Yue Meng, Kate Saenko, Aude Oliva, Rogerio Feris

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

1 code implementation ECCV 2020 Anelise Newman, Camilo Fosco, Vincent Casser, Allen Lee, Barry McNamara, Aude Oliva

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.

Predicting Visual Importance Across Graphic Design Types

no code implementations7 Aug 2020 Camilo Fosco, Vincent Casser, Amish Kumar Bedi, Peter O'Donovan, Aaron Hertzmann, Zoya Bylinskii

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.

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