Conference
BehAVE : behaviour alignment of video game encodings
| Τίτλος: | BehAVE : behaviour alignment of video game encodings |
|---|---|
| Συγγραφείς: | Rašajski, Nemanja, Trivedi, Chintan, Makantasis, Konstantinos, Liapis, Antonios, Yannakakis, Georgios N., ECCV Workshop on Computer Vision For Videogames |
| Στοιχεία εκδότη: | ECCV |
| Έτος έκδοσης: | 2024 |
| Συλλογή: | University of Malta: OAR@UM / L-Università ta' Malta |
| Θεματικοί όροι: | Artificial intelligence, Computer games -- Design, Computer games -- Programming |
| Περιγραφή: | Domain randomisation enhances the transferability of vision models across visually distinct domains with similar content. However, current methods heavily depend on intricate simulation engines, hampering feasibility and scalability. This paper introduces BehAVE , a video understanding framework that utilises existing commercial video games for domain randomisation without accessing their simulation engines. BehAVE taps into the visual diversity of video games for randomisation and uses textual descriptions of player actions to align videos with similar content. We evaluate BehAVE across 25 first-person shooter (FPS) games using various video and text foundation models, demonstrating its robustness in domain randomisation. BehAVE effectively aligns player behavioural patterns and achieves zero-shot transfer to multiple unseen FPS games when trained on just one game. In a more challenging scenario, BehAVE enhances the zero-shot transferability of foundation models to unseen FPS games, even when trained on a game of a different genre, with improvements of up to 22%. BehAVE is available online ; peer-reviewed |
| Τύπος εγγράφου: | conference object |
| Γλώσσα: | English |
| Relation: | https://www.um.edu.mt/library/oar/handle/123456789/135806 |
| Διαθεσιμότητα: | https://www.um.edu.mt/library/oar/handle/123456789/135806 |
| Rights: | info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. |
| Αριθμός Καταχώρησης: | edsbas.AEAD343F |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://www.um.edu.mt/library/oar/handle/123456789/135806# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: BehAVE : behaviour alignment of video game encodings – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rašajski%2C+Nemanja%22">Rašajski, Nemanja</searchLink><br /><searchLink fieldCode="AR" term="%22Trivedi%2C+Chintan%22">Trivedi, Chintan</searchLink><br /><searchLink fieldCode="AR" term="%22Makantasis%2C+Konstantinos%22">Makantasis, Konstantinos</searchLink><br /><searchLink fieldCode="AR" term="%22Liapis%2C+Antonios%22">Liapis, Antonios</searchLink><br /><searchLink fieldCode="AR" term="%22Yannakakis%2C+Georgios+N%2E%22">Yannakakis, Georgios N.</searchLink><br /><searchLink fieldCode="AR" term="%22ECCV+Workshop+on+Computer+Vision+For+Videogames%22">ECCV Workshop on Computer Vision For Videogames</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: ECCV – Name: DatePubCY Label: Publication Year Group: Date Data: 2024 – Name: Subset Label: Collection Group: HoldingsInfo Data: University of Malta: OAR@UM / L-Università ta' Malta – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+games+--+Design%22">Computer games -- Design</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+games+--+Programming%22">Computer games -- Programming</searchLink> – Name: Abstract Label: Description Group: Ab Data: Domain randomisation enhances the transferability of vision models across visually distinct domains with similar content. However, current methods heavily depend on intricate simulation engines, hampering feasibility and scalability. This paper introduces BehAVE , a video understanding framework that utilises existing commercial video games for domain randomisation without accessing their simulation engines. BehAVE taps into the visual diversity of video games for randomisation and uses textual descriptions of player actions to align videos with similar content. We evaluate BehAVE across 25 first-person shooter (FPS) games using various video and text foundation models, demonstrating its robustness in domain randomisation. BehAVE effectively aligns player behavioural patterns and achieves zero-shot transfer to multiple unseen FPS games when trained on just one game. In a more challenging scenario, BehAVE enhances the zero-shot transferability of foundation models to unseen FPS games, even when trained on a game of a different genre, with improvements of up to 22%. BehAVE is available online ; peer-reviewed – Name: TypeDocument Label: Document Type Group: TypDoc Data: conference object – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://www.um.edu.mt/library/oar/handle/123456789/135806 – Name: URL Label: Availability Group: URL Data: https://www.um.edu.mt/library/oar/handle/123456789/135806 – Name: Copyright Label: Rights Group: Cpyrght Data: info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. – Name: AN Label: Accession Number Group: ID Data: edsbas.AEAD343F |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Computer games -- Design Type: general – SubjectFull: Computer games -- Programming Type: general Titles: – TitleFull: BehAVE : behaviour alignment of video game encodings Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rašajski, Nemanja – PersonEntity: Name: NameFull: Trivedi, Chintan – PersonEntity: Name: NameFull: Makantasis, Konstantinos – PersonEntity: Name: NameFull: Liapis, Antonios – PersonEntity: Name: NameFull: Yannakakis, Georgios N. – PersonEntity: Name: NameFull: ECCV Workshop on Computer Vision For Videogames IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2024 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
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