Assessing the difficulty of predicting media memorability-Reference-Cited by-同舟云学术

Assessing the difficulty of predicting media memorability

Published:2023-09-20 Issue: Volume: Page:
ISSN:
Container-title:20th International Conference on Content-based Multimedia Indexing
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Author:

Constantin Mihai Gabriel¹^ORCID,Dogariu Mihai¹^ORCID,Jitaru Andrei Cosmin¹^ORCID,Ionescu Bogdan¹^ORCID

Affiliation:

1. AI Multimedia Lab, University Politehnica of Bucharest, RO

Funder

H2020

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3617233.3617270

Reference26 articles.

1. Muhammad Mustafa Ali Usmani , Sumaiyah Zahid , and Muhammad Atif Tahir . 2023 . Modelling of Video Memorability using Ensemble Learning and Transformers . In Working Notes Proceedings of the MediaEval 2022 Workshop. Muhammad Mustafa Ali Usmani, Sumaiyah Zahid, and Muhammad Atif Tahir. 2023. Modelling of Video Memorability using Ensemble Learning and Transformers. In Working Notes Proceedings of the MediaEval 2022 Workshop.

2. Mihai Gabriel Constantin and Bogdan Ionescu . 2023 . AIMultimediaLab at MediaEval 2022: Predicting Media Memorability Using Video Vision Transformers and Augmented Memorable Moments . In Working Notes Proceedings of the MediaEval 2022 Workshop. Mihai Gabriel Constantin and Bogdan Ionescu. 2023. AIMultimediaLab at MediaEval 2022: Predicting Media Memorability Using Video Vision Transformers and Augmented Memorable Moments. In Working Notes Proceedings of the MediaEval 2022 Workshop.

3. High level describable attributes for predicting aesthetics and interestingness

4. Human-Object Interaction: Application to Abandoned Luggage Detection in Video Surveillance Scenarios

5. What Makes an Object Memorable?