Matches in SemOpenAlex for { <https://semopenalex.org/work/W2948619611> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W2948619611 abstract "Photometric stereo estimates the surface normal given a set of images acquired under different illumination conditions. To deal with diverse factors involved in the image formation process, recent photometric stereo methods demand a large number of images as input. We propose a method that can dramatically decrease the demands on the number of images by learning the most informative ones under different illumination conditions. To this end, we use a deep learning framework to automatically learn the critical illumination conditions required at input. Furthermore, we present an occlusion layer that can synthesize cast shadows, which effectively improves the estimation accuracy. We assess our method on challenging real-world conditions, where we outperform techniques elsewhere in the literature with a significantly reduced number of light conditions." @default.
- W2948619611 created "2019-06-14" @default.
- W2948619611 creator A5003277535 @default.
- W2948619611 creator A5007075649 @default.
- W2948619611 creator A5010621788 @default.
- W2948619611 creator A5033986386 @default.
- W2948619611 date "2019-06-01" @default.
- W2948619611 modified "2023-10-10" @default.
- W2948619611 title "Learning to Minify Photometric Stereo" @default.
- W2948619611 cites W1975089519 @default.
- W2948619611 cites W1978356057 @default.
- W2948619611 cites W2021398211 @default.
- W2948619611 cites W2076130323 @default.
- W2948619611 cites W2112417771 @default.
- W2948619611 cites W2122468143 @default.
- W2948619611 cites W2142181854 @default.
- W2948619611 cites W2165192967 @default.
- W2948619611 cites W2736951491 @default.
- W2948619611 cites W2766067961 @default.
- W2948619611 cites W2810337759 @default.
- W2948619611 cites W2887502697 @default.
- W2948619611 cites W2963446712 @default.
- W2948619611 cites W2963820554 @default.
- W2948619611 cites W3005895305 @default.
- W2948619611 doi "https://doi.org/10.1109/cvpr.2019.00775" @default.
- W2948619611 hasPublicationYear "2019" @default.
- W2948619611 type Work @default.
- W2948619611 sameAs 2948619611 @default.
- W2948619611 citedByCount "43" @default.
- W2948619611 countsByYear W29486196112020 @default.
- W2948619611 countsByYear W29486196112021 @default.
- W2948619611 countsByYear W29486196112022 @default.
- W2948619611 countsByYear W29486196112023 @default.
- W2948619611 crossrefType "proceedings-article" @default.
- W2948619611 hasAuthorship W2948619611A5003277535 @default.
- W2948619611 hasAuthorship W2948619611A5007075649 @default.
- W2948619611 hasAuthorship W2948619611A5010621788 @default.
- W2948619611 hasAuthorship W2948619611A5033986386 @default.
- W2948619611 hasBestOaLocation W29486196112 @default.
- W2948619611 hasConcept C108583219 @default.
- W2948619611 hasConcept C111919701 @default.
- W2948619611 hasConcept C115961682 @default.
- W2948619611 hasConcept C154945302 @default.
- W2948619611 hasConcept C177264268 @default.
- W2948619611 hasConcept C199360897 @default.
- W2948619611 hasConcept C31972630 @default.
- W2948619611 hasConcept C41008148 @default.
- W2948619611 hasConcept C44365914 @default.
- W2948619611 hasConcept C68537008 @default.
- W2948619611 hasConcept C98045186 @default.
- W2948619611 hasConceptScore W2948619611C108583219 @default.
- W2948619611 hasConceptScore W2948619611C111919701 @default.
- W2948619611 hasConceptScore W2948619611C115961682 @default.
- W2948619611 hasConceptScore W2948619611C154945302 @default.
- W2948619611 hasConceptScore W2948619611C177264268 @default.
- W2948619611 hasConceptScore W2948619611C199360897 @default.
- W2948619611 hasConceptScore W2948619611C31972630 @default.
- W2948619611 hasConceptScore W2948619611C41008148 @default.
- W2948619611 hasConceptScore W2948619611C44365914 @default.
- W2948619611 hasConceptScore W2948619611C68537008 @default.
- W2948619611 hasConceptScore W2948619611C98045186 @default.
- W2948619611 hasLocation W29486196111 @default.
- W2948619611 hasLocation W29486196112 @default.
- W2948619611 hasLocation W29486196113 @default.
- W2948619611 hasOpenAccess W2948619611 @default.
- W2948619611 hasPrimaryLocation W29486196111 @default.
- W2948619611 hasRelatedWork W1554604122 @default.
- W2948619611 hasRelatedWork W2103381853 @default.
- W2948619611 hasRelatedWork W2138334472 @default.
- W2948619611 hasRelatedWork W2152466583 @default.
- W2948619611 hasRelatedWork W2156736396 @default.
- W2948619611 hasRelatedWork W2158018118 @default.
- W2948619611 hasRelatedWork W2161229648 @default.
- W2948619611 hasRelatedWork W2390004782 @default.
- W2948619611 hasRelatedWork W2744088300 @default.
- W2948619611 hasRelatedWork W3045199074 @default.
- W2948619611 isParatext "false" @default.
- W2948619611 isRetracted "false" @default.
- W2948619611 magId "2948619611" @default.
- W2948619611 workType "article" @default.