Matches in SemOpenAlex for { <https://semopenalex.org/work/W2951810985> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W2951810985 abstract "We present a simple and efficient method based on deep learning to automatically decompose sketched objects into semantically valid parts. We train a deep neural network to transfer existing segmentations and labelings from 3D models to freehand sketches without requiring numerous well-annotated sketches as training data. The network takes the binary image of a sketched object as input and produces a corresponding segmentation map with per-pixel labelings as output. A subsequent post-process procedure with multi-label graph cuts further refines the segmentation and labeling result. We validate our proposed method on two sketch datasets. Experiments show that our method outperforms the state-of-the-art method in terms of segmentation and labeling accuracy and is significantly faster, enabling further integration in interactive drawing systems. We demonstrate the efficiency of our method in a sketch-based modeling application that automatically transforms input sketches into 3D models by part assembly." @default.
- W2951810985 created "2019-06-27" @default.
- W2951810985 creator A5008384374 @default.
- W2951810985 creator A5018275477 @default.
- W2951810985 creator A5052692924 @default.
- W2951810985 date "2018-07-31" @default.
- W2951810985 modified "2023-10-01" @default.
- W2951810985 title "Fast Sketch Segmentation and Labeling with Deep Learning" @default.
- W2951810985 cites W1901129140 @default.
- W2951810985 cites W1903029394 @default.
- W2951810985 cites W1972420097 @default.
- W2951810985 cites W1973212109 @default.
- W2951810985 cites W2012785966 @default.
- W2951810985 cites W2063844773 @default.
- W2951810985 cites W2079442992 @default.
- W2951810985 cites W2101309634 @default.
- W2951810985 cites W2143549856 @default.
- W2951810985 cites W2161141071 @default.
- W2951810985 cites W2496271548 @default.
- W2951810985 cites W2553307952 @default.
- W2951810985 cites W2559219295 @default.
- W2951810985 cites W2753386433 @default.
- W2951810985 cites W2963073614 @default.
- W2951810985 cites W2963881378 @default.
- W2951810985 doi "https://doi.org/10.48550/arxiv.1807.11847" @default.
- W2951810985 hasPublicationYear "2018" @default.
- W2951810985 type Work @default.
- W2951810985 sameAs 2951810985 @default.
- W2951810985 citedByCount "1" @default.
- W2951810985 countsByYear W29518109852018 @default.
- W2951810985 crossrefType "posted-content" @default.
- W2951810985 hasAuthorship W2951810985A5008384374 @default.
- W2951810985 hasAuthorship W2951810985A5018275477 @default.
- W2951810985 hasAuthorship W2951810985A5052692924 @default.
- W2951810985 hasBestOaLocation W29518109851 @default.
- W2951810985 hasConcept C108583219 @default.
- W2951810985 hasConcept C111919701 @default.
- W2951810985 hasConcept C11413529 @default.
- W2951810985 hasConcept C124504099 @default.
- W2951810985 hasConcept C132525143 @default.
- W2951810985 hasConcept C153180895 @default.
- W2951810985 hasConcept C154945302 @default.
- W2951810985 hasConcept C2779231336 @default.
- W2951810985 hasConcept C2781238097 @default.
- W2951810985 hasConcept C2984842247 @default.
- W2951810985 hasConcept C31972630 @default.
- W2951810985 hasConcept C33923547 @default.
- W2951810985 hasConcept C41008148 @default.
- W2951810985 hasConcept C48372109 @default.
- W2951810985 hasConcept C50644808 @default.
- W2951810985 hasConcept C5134670 @default.
- W2951810985 hasConcept C80444323 @default.
- W2951810985 hasConcept C89600930 @default.
- W2951810985 hasConcept C94375191 @default.
- W2951810985 hasConcept C98045186 @default.
- W2951810985 hasConceptScore W2951810985C108583219 @default.
- W2951810985 hasConceptScore W2951810985C111919701 @default.
- W2951810985 hasConceptScore W2951810985C11413529 @default.
- W2951810985 hasConceptScore W2951810985C124504099 @default.
- W2951810985 hasConceptScore W2951810985C132525143 @default.
- W2951810985 hasConceptScore W2951810985C153180895 @default.
- W2951810985 hasConceptScore W2951810985C154945302 @default.
- W2951810985 hasConceptScore W2951810985C2779231336 @default.
- W2951810985 hasConceptScore W2951810985C2781238097 @default.
- W2951810985 hasConceptScore W2951810985C2984842247 @default.
- W2951810985 hasConceptScore W2951810985C31972630 @default.
- W2951810985 hasConceptScore W2951810985C33923547 @default.
- W2951810985 hasConceptScore W2951810985C41008148 @default.
- W2951810985 hasConceptScore W2951810985C48372109 @default.
- W2951810985 hasConceptScore W2951810985C50644808 @default.
- W2951810985 hasConceptScore W2951810985C5134670 @default.
- W2951810985 hasConceptScore W2951810985C80444323 @default.
- W2951810985 hasConceptScore W2951810985C89600930 @default.
- W2951810985 hasConceptScore W2951810985C94375191 @default.
- W2951810985 hasConceptScore W2951810985C98045186 @default.
- W2951810985 hasLocation W29518109851 @default.
- W2951810985 hasOpenAccess W2951810985 @default.
- W2951810985 hasPrimaryLocation W29518109851 @default.
- W2951810985 hasRelatedWork W1669643531 @default.
- W2951810985 hasRelatedWork W1963494852 @default.
- W2951810985 hasRelatedWork W2019566805 @default.
- W2951810985 hasRelatedWork W2101128524 @default.
- W2951810985 hasRelatedWork W2110230079 @default.
- W2951810985 hasRelatedWork W2383464976 @default.
- W2951810985 hasRelatedWork W2960184797 @default.
- W2951810985 hasRelatedWork W2972093541 @default.
- W2951810985 hasRelatedWork W4285827401 @default.
- W2951810985 hasRelatedWork W1967061043 @default.
- W2951810985 isParatext "false" @default.
- W2951810985 isRetracted "false" @default.
- W2951810985 magId "2951810985" @default.
- W2951810985 workType "article" @default.