Matches in SemOpenAlex for { <https://semopenalex.org/work/W4207040532> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W4207040532 endingPage "371" @default.
- W4207040532 startingPage "353" @default.
- W4207040532 abstract "Object pose estimation is a key perceptual capability in robotics. We propose a fully-convolutional extension of the PoseCNN method, which densely predicts object translations and orientations. This has several advantages such as improving the spatial resolution of the orientation predictions—useful in highly-cluttered arrangements, significant reduction in parameters by avoiding full connectivity, and fast inference. We propose and discuss several aggregation methods for dense orientation predictions that can be applied as a post-processing step, such as averaging and clustering techniques. We demonstrate that our method achieves the same accuracy as PoseCNN on the challenging YCB-Video dataset and provide a detailed ablation study of several variants of our method. Finally, we demonstrate that the model can be further improved by inserting an iterative refinement module into the middle of the network, which enforces consistency of the prediction." @default.
- W4207040532 created "2022-01-26" @default.
- W4207040532 creator A5004710550 @default.
- W4207040532 creator A5007129803 @default.
- W4207040532 creator A5023789533 @default.
- W4207040532 creator A5027761977 @default.
- W4207040532 date "2022-01-01" @default.
- W4207040532 modified "2023-09-28" @default.
- W4207040532 title "ConvPoseCNN2: Prediction and Refinement of Dense 6D Object Pose" @default.
- W4207040532 cites W1536680647 @default.
- W4207040532 cites W1855641990 @default.
- W4207040532 cites W2245493112 @default.
- W4207040532 cites W2472269674 @default.
- W4207040532 cites W2604236302 @default.
- W4207040532 cites W2768879211 @default.
- W4207040532 cites W2797394534 @default.
- W4207040532 cites W2950921159 @default.
- W4207040532 cites W2962783853 @default.
- W4207040532 cites W2962956488 @default.
- W4207040532 cites W2963037989 @default.
- W4207040532 cites W2963188159 @default.
- W4207040532 cites W2963351448 @default.
- W4207040532 cites W3010769982 @default.
- W4207040532 cites W3011171290 @default.
- W4207040532 cites W4246449400 @default.
- W4207040532 doi "https://doi.org/10.1007/978-3-030-94893-1_16" @default.
- W4207040532 hasPublicationYear "2022" @default.
- W4207040532 type Work @default.
- W4207040532 citedByCount "0" @default.
- W4207040532 crossrefType "book-chapter" @default.
- W4207040532 hasAuthorship W4207040532A5004710550 @default.
- W4207040532 hasAuthorship W4207040532A5007129803 @default.
- W4207040532 hasAuthorship W4207040532A5023789533 @default.
- W4207040532 hasAuthorship W4207040532A5027761977 @default.
- W4207040532 hasBestOaLocation W42070405322 @default.
- W4207040532 hasConcept C153180895 @default.
- W4207040532 hasConcept C154945302 @default.
- W4207040532 hasConcept C16345878 @default.
- W4207040532 hasConcept C2524010 @default.
- W4207040532 hasConcept C26517878 @default.
- W4207040532 hasConcept C2776214188 @default.
- W4207040532 hasConcept C2776436953 @default.
- W4207040532 hasConcept C2781238097 @default.
- W4207040532 hasConcept C31972630 @default.
- W4207040532 hasConcept C33923547 @default.
- W4207040532 hasConcept C38652104 @default.
- W4207040532 hasConcept C41008148 @default.
- W4207040532 hasConcept C52102323 @default.
- W4207040532 hasConcept C73555534 @default.
- W4207040532 hasConcept C81363708 @default.
- W4207040532 hasConceptScore W4207040532C153180895 @default.
- W4207040532 hasConceptScore W4207040532C154945302 @default.
- W4207040532 hasConceptScore W4207040532C16345878 @default.
- W4207040532 hasConceptScore W4207040532C2524010 @default.
- W4207040532 hasConceptScore W4207040532C26517878 @default.
- W4207040532 hasConceptScore W4207040532C2776214188 @default.
- W4207040532 hasConceptScore W4207040532C2776436953 @default.
- W4207040532 hasConceptScore W4207040532C2781238097 @default.
- W4207040532 hasConceptScore W4207040532C31972630 @default.
- W4207040532 hasConceptScore W4207040532C33923547 @default.
- W4207040532 hasConceptScore W4207040532C38652104 @default.
- W4207040532 hasConceptScore W4207040532C41008148 @default.
- W4207040532 hasConceptScore W4207040532C52102323 @default.
- W4207040532 hasConceptScore W4207040532C73555534 @default.
- W4207040532 hasConceptScore W4207040532C81363708 @default.
- W4207040532 hasLocation W42070405321 @default.
- W4207040532 hasLocation W42070405322 @default.
- W4207040532 hasOpenAccess W4207040532 @default.
- W4207040532 hasPrimaryLocation W42070405321 @default.
- W4207040532 hasRelatedWork W1537622850 @default.
- W4207040532 hasRelatedWork W1726816713 @default.
- W4207040532 hasRelatedWork W2026349903 @default.
- W4207040532 hasRelatedWork W2766932195 @default.
- W4207040532 hasRelatedWork W2770260910 @default.
- W4207040532 hasRelatedWork W2786068778 @default.
- W4207040532 hasRelatedWork W2956571887 @default.
- W4207040532 hasRelatedWork W3089100170 @default.
- W4207040532 hasRelatedWork W3108980762 @default.
- W4207040532 hasRelatedWork W842220368 @default.
- W4207040532 isParatext "false" @default.
- W4207040532 isRetracted "false" @default.
- W4207040532 workType "book-chapter" @default.