A benchmark of light field view interpolation methods
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Publication Date
2020-07-01Journal Title
2020 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2020
ISBN
9781728114859
Type
Conference Object
This Version
AM
Metadata
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Yue, D., Khan Gul, M., Batz, M., Keinert, J., & Mantiuk, R. (2020). A benchmark of light field view interpolation methods. 2020 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2020 https://doi.org/10.1109/ICMEW46912.2020.9106041
Abstract
Light field view interpolation provides a solution that reduces the prohibitive size of a dense light field. This paper examines state-ofthe-art light field view interpolation methods with a comprehensive benchmark on challenging scenarios specific for interpolation tasks. Each method is analyzed in terms of their strengths and weaknesses in handling different challenges. We find that large disparities in a scene are the main source of challenge for the light field view interpolation methods. We also find that a basic backward warping based on the depth estimation from optical flow provides comparable performance against usually complex learning-based methods.
Relationships
Is supplemented by: https://doi.org/10.17863/CAM.52226
Sponsorship
European Commission Horizon 2020 (H2020) ERC (725253)
European Commission Horizon 2020 (H2020) Marie Sklodowska-Curie actions (765911)
Embargo Lift Date
2021-07-01
Identifiers
External DOI: https://doi.org/10.1109/ICMEW46912.2020.9106041
This record's URL: https://www.repository.cam.ac.uk/handle/1810/305269
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