Linking WordNet to 3D Shapes
Angel X Chang, Rishi Mago, Pranav Krishna, Manolis Savva, Christiane Fellbaum
Abstract
We describe a project to link the Princeton WordNet to 3D representations of real objects and scenes. The goal is to establish a dataset that helps us to understand how people categorize everyday common objects via their parts, attributes, and context. This paper describes the annotation and data collection effort so far as well as ideas for future work.- Anthology ID:
- 2018.gwc-1.44
- Volume:
- Proceedings of the 9th Global Wordnet Conference
- Month:
- January
- Year:
- 2018
- Address:
- Nanyang Technological University (NTU), Singapore
- Editors:
- Francis Bond, Piek Vossen, Christiane Fellbaum
- Venue:
- GWC
- SIG:
- SIGLEX
- Publisher:
- Global Wordnet Association
- Note:
- Pages:
- 358–363
- Language:
- URL:
- https://aclanthology.org/2018.gwc-1.44
- DOI:
- Cite (ACL):
- Angel X Chang, Rishi Mago, Pranav Krishna, Manolis Savva, and Christiane Fellbaum. 2018. Linking WordNet to 3D Shapes. In Proceedings of the 9th Global Wordnet Conference, pages 358–363, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.
- Cite (Informal):
- Linking WordNet to 3D Shapes (Chang et al., GWC 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2018.gwc-1.44.pdf
- Data
- ImageNet, SUNCG, ShapeNet