FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2886553614> ?p ?o ?g. }

• W2886553614 endingPage "279" @default.
• W2886553614 startingPage "271" @default.
• W2886553614 abstract "Scene extrapolation is a challenging variant of the scene completion problem, which pertains to predicting the missing part(s) of a scene. While the 3D scene completion algorithms in the literature try to fill the occluded part of a scene such as a chair behind a table, we focus on extrapolating the available half-scene information to a full one, a problem that, to our knowledge, has not been studied yet. Our approaches are based on convolutional neural networks (CNN). As input, we take the half of 3D voxelized scenes, then our models complete the other half of scenes as output. Our baseline CNN model consisting of convolutional and ReLU layers with multiple residual connections and Softmax classifier with voxel-wise cross-entropy loss function at the end. We train and evaluate our models on the synthetic 3D SUNCG dataset. We show that our trained networks can predict the other half of the scenes and complete the objects correctly with suitable lengths. With a discussion on the challenges, we propose scene extrapolation as a challenging test bed for future research in deep learning. We made our models available on https://github.com/aliabbasi/d3dsse ." @default.
• W2886553614 created "2018-08-22" @default.
• W2886553614 creator A5007503075 @default.
• W2886553614 creator A5032424779 @default.
• W2886553614 creator A5052083145 @default.
• W2886553614 date "2018-08-17" @default.
• W2886553614 modified "2023-10-16" @default.
• W2886553614 title "Deep 3D semantic scene extrapolation" @default.
• W2886553614 cites W1901129140 @default.
• W2886553614 cites W1967577110 @default.
• W2886553614 cites W1981349497 @default.
• W2886553614 cites W1981940178 @default.
• W2886553614 cites W1992642990 @default.
• W2886553614 cites W1995628331 @default.
• W2886553614 cites W2034950486 @default.
• W2886553614 cites W2049981393 @default.
• W2886553614 cites W2052086995 @default.
• W2886553614 cites W2060268527 @default.
• W2886553614 cites W2107302003 @default.
• W2886553614 cites W2112796928 @default.
• W2886553614 cites W2127431937 @default.
• W2886553614 cites W2131697568 @default.
• W2886553614 cites W2142325307 @default.
• W2886553614 cites W2162559028 @default.
• W2886553614 cites W2164135471 @default.
• W2886553614 cites W2164490837 @default.
• W2886553614 cites W2170490343 @default.
• W2886553614 cites W2194775991 @default.
• W2886553614 cites W2264132031 @default.
• W2886553614 cites W2337420161 @default.
• W2886553614 cites W2344109021 @default.
• W2886553614 cites W2444097022 @default.
• W2886553614 cites W2509413994 @default.
• W2886553614 cites W2549139847 @default.
• W2886553614 cites W2557465155 @default.
• W2886553614 cites W2559882727 @default.
• W2886553614 cites W2611104282 @default.
• W2886553614 cites W2738406145 @default.
• W2886553614 cites W2738588019 @default.
• W2886553614 cites W2963351448 @default.
• W2886553614 cites W2963735494 @default.
• W2886553614 cites W2963917315 @default.
• W2886553614 cites W2964024144 @default.
• W2886553614 cites W4240726888 @default.
• W2886553614 doi "https://doi.org/10.1007/s00371-018-1586-7" @default.
• W2886553614 hasPublicationYear "2018" @default.
• W2886553614 type Work @default.
• W2886553614 sameAs 2886553614 @default.
• W2886553614 citedByCount "9" @default.
• W2886553614 countsByYear W28865536142018 @default.
• W2886553614 countsByYear W28865536142020 @default.
• W2886553614 countsByYear W28865536142021 @default.
• W2886553614 countsByYear W28865536142022 @default.
• W2886553614 countsByYear W28865536142023 @default.
• W2886553614 crossrefType "journal-article" @default.
• W2886553614 hasAuthorship W2886553614A5007503075 @default.
• W2886553614 hasAuthorship W2886553614A5032424779 @default.
• W2886553614 hasAuthorship W2886553614A5052083145 @default.
• W2886553614 hasBestOaLocation W28865536142 @default.
• W2886553614 hasConcept C108583219 @default.
• W2886553614 hasConcept C11413529 @default.
• W2886553614 hasConcept C120665830 @default.
• W2886553614 hasConcept C121332964 @default.
• W2886553614 hasConcept C132459708 @default.
• W2886553614 hasConcept C134306372 @default.
• W2886553614 hasConcept C153180895 @default.
• W2886553614 hasConcept C154945302 @default.
• W2886553614 hasConcept C155512373 @default.
• W2886553614 hasConcept C169760540 @default.
• W2886553614 hasConcept C188441871 @default.
• W2886553614 hasConcept C192209626 @default.
• W2886553614 hasConcept C197654239 @default.
• W2886553614 hasConcept C26760741 @default.
• W2886553614 hasConcept C31972630 @default.
• W2886553614 hasConcept C33923547 @default.
• W2886553614 hasConcept C41008148 @default.
• W2886553614 hasConcept C54170458 @default.
• W2886553614 hasConcept C77660652 @default.
• W2886553614 hasConcept C81363708 @default.
• W2886553614 hasConcept C86803240 @default.
• W2886553614 hasConcept C95623464 @default.
• W2886553614 hasConceptScore W2886553614C108583219 @default.
• W2886553614 hasConceptScore W2886553614C11413529 @default.
• W2886553614 hasConceptScore W2886553614C120665830 @default.
• W2886553614 hasConceptScore W2886553614C121332964 @default.
• W2886553614 hasConceptScore W2886553614C132459708 @default.
• W2886553614 hasConceptScore W2886553614C134306372 @default.
• W2886553614 hasConceptScore W2886553614C153180895 @default.
• W2886553614 hasConceptScore W2886553614C154945302 @default.
• W2886553614 hasConceptScore W2886553614C155512373 @default.
• W2886553614 hasConceptScore W2886553614C169760540 @default.
• W2886553614 hasConceptScore W2886553614C188441871 @default.
• W2886553614 hasConceptScore W2886553614C192209626 @default.
• W2886553614 hasConceptScore W2886553614C197654239 @default.
• W2886553614 hasConceptScore W2886553614C26760741 @default.
• W2886553614 hasConceptScore W2886553614C31972630 @default.
• W2886553614 hasConceptScore W2886553614C33923547 @default.
• W2886553614 hasConceptScore W2886553614C41008148 @default.

• next