Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Constantin, Mihai Gabriel"'
Autor:
Ştefan, Liviu-Daniel, Stanciu, Dan-Cristian, Dogariu, Mihai, Constantin, Mihai Gabriel, Jitaru, Andrei Cosmin, Ionescu, Bogdan
Recent advancements in Generative Adversarial Networks (GANs) have enabled photorealistic image generation with high quality. However, the malicious use of such generated media has raised concerns regarding visual misinformation. Although deepfake de
Externí odkaz:
http://arxiv.org/abs/2404.00114
Autor:
Sweeney, Lorin, Constantin, Mihai Gabriel, Demarty, Claire-Hélène, Fosco, Camilo, de Herrera, Alba G. Seco, Halder, Sebastian, Healy, Graham, Ionescu, Bogdan, Matran-Fernandez, Ana, Smeaton, Alan F., Sultana, Mushfika
This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022. This year we have reorganised and simplified the task in order to lubricate a greater depth of inquiry. Similar to last year, two datasets are pr
Externí odkaz:
http://arxiv.org/abs/2212.06516
Autor:
de Herrera, Alba García Deco, Constantin, Mihai Gabriel, Demarty, Chaire-Hélène, Fosco, Camilo, Halder, Sebastian, Healy, Graham, Ionescu, Bogdan, Matran-Fernandez, Ana, Smeaton, Alan F., Sultana, Mushfika, Sweeney, Lorin
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. This has allowed us to compare the performance of many memorabilit
Externí odkaz:
http://arxiv.org/abs/2212.03955
Autor:
Kiziltepe, Rukiye Savran, Constantin, Mihai Gabriel, Demarty, Claire-Helene, Healy, Graham, Fosco, Camilo, de Herrera, Alba Garcia Seco, Halder, Sebastian, Ionescu, Bogdan, Matran-Fernandez, Ana, Smeaton, Alan F., Sweeney, Lorin
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. In 2021, two datasets of videos are used:
Externí odkaz:
http://arxiv.org/abs/2112.05982
Autor:
Kiziltepe, Rukiye Savran, Sweeney, Lorin, Constantin, Mihai Gabriel, Doctor, Faiyaz, de Herrera, Alba Garcia Seco, Demarty, Claire-Helene, Healy, Graham, Ionescu, Bogdan, Smeaton, Alan F.
Publikováno v:
Data in Brief, Volume 39, 107671, (2021), ISSN 2352-3409
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 anno
Externí odkaz:
http://arxiv.org/abs/2112.02303
Autor:
De Herrera, Alba García Seco, Kiziltepe, Rukiye Savran, Chamberlain, Jon, Constantin, Mihai Gabriel, Demarty, Claire-Hélène, Doctor, Faiyaz, Ionescu, Bogdan, Smeaton, Alan F.
Publikováno v:
MediaEval Multimedia Benchmark Workshop Working Notes, 14-15 December 2020
This paper describes the MediaEval 2020 \textit{Predicting Media Memorability} task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term v
Externí odkaz:
http://arxiv.org/abs/2012.15650
Autor:
García Seco de Herrera, Alba, Constantin, Mihai Gabriel, Demarty, Claire-Hélène, Fosco, Camilo, Halder, Sebastian, Healy, Graham, Ionescu, Bogdan, Matran-Fernandez, Ana, Smeaton, Alan F., Sultana, Mushfika, Sweeney, Lorin
Publikováno v:
García Seco de Herrera, Alba ORCID: 0000-0002-6509-5325 , Constantin, Mihai Gabriel ORCID: 0000-0002-2312-6672 , Demarty, Claire-Hélène, Fosco, Camilo, Halder, Sebastian ORCID: 0000-0003-1017-3696 , Healy, Graham ORCID: 0000-0001-6429-6339 , Ionescu, Bogdan, Matran-Fernandez, Ana ORCID: 0000-0002-8409-3747 , Smeaton, Alan F. ORCID: 0000-0003-1028-8389 , Sultana, Mushfika and Sweeney, Lorin ORCID: 0000-0002-3427-1250 (2022) Experiences from the MediaEval predicting media memorability task. In: The NeurIPS Memory in Artificial and Real Intelligence (MemARI) Workshop, 2 Dec 2022, New Orleans, USA.
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. This has allowed us to compare the performance of many memorabilit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41fc28ade9ebe8f827a9008ae24430f1
http://arxiv.org/abs/2212.03955
http://arxiv.org/abs/2212.03955
Autor:
Constantin, Mihai Gabriel1 (AUTHOR) mgconstantin@imag.pub.ro, Ştefan, Liviu-Daniel1 (AUTHOR), Ionescu, Bogdan1 (AUTHOR), Duong, Ngoc Q. K.2 (AUTHOR), Demarty, Claire-Héléne2 (AUTHOR), Sjöberg, Mats3 (AUTHOR)
Publikováno v:
International Journal of Computer Vision. May2021, Vol. 129 Issue 5, p1526-1550. 25p.
Publikováno v:
ACM Computing Surveys. Mar2020, Vol. 52 Issue 2, p1-37. 37p. 2 Charts.
Autor:
De Herrera, Alba García Seco, Kiziltepe, Rukiye Savran, Chamberlain, Jon, Constantin, Mihai Gabriel, Demarty, Claire-Hélène, Doctor, Faiyaz, Ionescu, Bogdan, Smeaton, Alan F.
Publikováno v:
de Herrera, Alba G. Seco ORCID: 0000-0002-6509-5325 , Kiziltepe, Rukiye Savran ORCID: 0000-0002-3862-7621 , Chamberlain, Jon ORCID: 0000-0002-6947-8964 , Constantin, Mihai Gabriel ORCID: 0000-0002-2312-6672 , Demarty, Claire-Hélène, Doctor, Faiyaz ORCID: 0000-0002-8412-5489 , Ionescu, Bogdan ORCID: 0000-0003-4112-5769 and Smeaton, Alan F. ORCID: 0000-0003-1028-8389 (2020) Overview of MediaEval 2020 predicting media memorability task: what makes a video memorable? In: MediaEval 2020 Multimedia Benchmark Workshop, 14-15 Dec 2020, Online.
This paper describes the MediaEval 2020 \textit{Predicting Media Memorability} task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e64f1e4f499afc815ea2a557aac16c2