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CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2095190799

CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

About this item

Full title

CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

Author / Creator

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2018-12

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

Scope and Contents

Contents

Intrinsic image decomposition is a challenging, long-standing computer vision problem for which ground truth data is very difficult to acquire. We explore the use of synthetic data for training CNN-based intrinsic image decomposition models, then applying these learned models to real-world images. To that end, we present \ICG, a new, large-scale da...

Alternative Titles

Full title

CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2095190799

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2095190799

Other Identifiers

E-ISSN

2331-8422

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