End-to-End Depth-Guided Relighting Using Lightweight Deep Learning-Based Method
End-to-End Depth-Guided Relighting Using Lightweight Deep Learning-Based Method
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Image relighting, which involves modifying the lighting conditions while preserving the visual content, is fundamental to computer vision. This study introduced a bi-modal lightweight deep learning model for depth-guided relighting. The model utilizes the Res2Net Squeezed block’s ability to capture long-range dependencies and to enhance feature rep...
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Full title
End-to-End Depth-Guided Relighting Using Lightweight Deep Learning-Based Method
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TN_cdi_doaj_primary_oai_doaj_org_article_4b0a6fe4ed6945c989fe06d9c3b86584
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4b0a6fe4ed6945c989fe06d9c3b86584
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ISSN
2313-433X
E-ISSN
2313-433X
DOI
10.3390/jimaging9090175
