VidHarm: A Clip Based Dataset for Harmful Content Detection

Edstedt, Johan (author): Linköpings universitet,Datorseende,Tekniska fakulteten

Berg, Amanda (author): Linköpings universitet,Datorseende,Tekniska fakulteten

Felsberg, Michael (author): Linköpings universitet,Datorseende,Tekniska fakulteten

Karlsson, Johan (author): Statens Medieråd, Stockholm,Statens Medierad, Sweden

Benavente, Francisca (author): Statens Medieråd, Stockholm,Statens Medierad, Sweden

Novak, Anette (author): Statens Medieråd, Stockholm,Statens Medierad, Sweden

Grund Pihlgren, Gustav, 1994- (author): Luleå tekniska universitet,EISLAB,Lulea Univ Technol, Sweden

(creator_code:org_t)

Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
English.
In: 2022 26th International Conference on Pattern Recognition (ICPR). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665490627 - 9781665490634 ; , s. 1543-1549

Related links:: https://urn.kb.se/re...; show more...; https://doi.org/10.1...; https://urn.kb.se/re...; show less...

Abstract Subject headings

Automatically identifying harmful content in video is an important task with a wide range of applications. However, there is a lack of professionally labeled open datasets available. In this work VidHarm, an open dataset of 3589 video clips from film trailers annotated by professionals, is presented. An analysis of the dataset is performed, revealing among other things the relation between clip and trailer level annotations. Audiovisual models are trained on the dataset and an in-depth study of modeling choices conducted. The results show that performance is greatly improved by combining the visual and audio modality, pre-training on large-scale video recognition datasets, and class balanced sampling. Lastly, biases of the trained models are investigated using discrimination probing.VidHarm is openly available, and further details are available at the webpage https://vidharm.github.io/

NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

By the author/editor: Edstedt, Johan; Berg, Amanda; Felsberg, Michae ...; Karlsson, Johan; Benavente, Franc ...; Novak, Anette; show more...; Grund Pihlgren, ...; show less...

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Vision ...

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Science ...

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