Investigating pretrained self-supervised vision transformers for reference-based quality assessment 2023 (English)Conference paper, Published paper (Refereed)

Place, publisher, year, edition, pages

Society for Imaging Science and Technology , 2023. Vol. 35, article id IQSP-308

Series

IS&T International Symposium on Electronic Imaging Science and Technology, E-ISSN 2470-1173

Keywords [en]

Full-reference Image Quality Assessment, Vision Transformers, Self-Supervised Learning (DINO)

National Category

Computer graphics and computer vision Computer Sciences

Research subject

Machine Learning

Identifiers

URN: urn:nbn:se:ltu:diva-103562DOI: 10.2352/EI.2023.35.8.IQSP-308Scopus ID: 2-s2.0-85169569117OAI: oai:DiVA.org:ltu-103562DiVA, id: diva2:1826836

Conference

IS and T International Symposium on Electronic Imaging: 20th Image Quality and System Performance, IQSP 2023, San Francisco, United States, January 16-19, 2023

Available from: 2024-01-12 Created: 2024-01-12 Last updated: 2025-02-01Bibliographically approved

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Authority records

De, Kanjar

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De, Kanjar

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Embedded Internet Systems Lab

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Computer graphics and computer visionComputer Sciences

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