WildDeepfake: a challenging real-world dataset for deepfake detection

Zi, B; Chang, M; Chen, J; Ma, Daniel; Jiang, Y G

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WildDeepfake: a challenging real-world dataset for deepfake detection

conference contribution

posted on 2020-10-01, 00:00 authored by B Zi, M Chang, J Chen, Daniel Ma, Y G Jiang

WildDeepfake: a challenging real-world dataset for deepfake detection

History

Event

Association for Computing Machinery. Conference (28th : 2020 : Seattle, Washington)

Series

Association for Computing Machinery Conference

Pagination

2382 - 2390

Publisher

Association for Computing Machinery

Location

Seattle, Washington

Place of publication

New York, N.Y.

Publisher DOI

https://doi.org/10.1145/3394171.3413769

Start date

2020-10-12

End date

2020-10-16

ISBN-13

9781450379885

Language

eng

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

C Chen, R Cucchiara, X-S Hua, G-J Qi, E Ricci, Z Zhang, R Zimmermann, P Atrey, Z Li

Title of proceedings

MM 2020 : Proceedings of the 28th ACM International Conference on Multimedia

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WildDeepfake: a challenging real-world dataset for deepfake detection

File(s) under permanent embargo

WildDeepfake: a challenging real-world dataset for deepfake detection

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Place of publication

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