Title
Cross-Modal Attribute Transfer for Rescaling 3D Models
Abstract
We present an algorithm for transferring physical attributes between webpages and 3D shapes. We crawl product catalogues and other webpages with structured metadata containing physical attributes such as dimensions and weights. Then we transfer physical attributes between shapes and real-world objects using a joint embedding of images and 3D shapes and a view-based weighting and aspect ratio filtering scheme for instance-level linking of 3D models and real-world counterpart objects. We evaluate our approach on a large-scale dataset of unscaled 3D models, and show that we outperform prior work on rescaling 3D models that considers only category-level size priors.
Year
DOI
Venue
2017
10.1109/3DV.2017.00078
2017 International Conference on 3D Vision (3DV)
Keywords
Field
DocType
3D-models,metric-size-prediction,cross-modal-attribute-transfer
Metadata,Weighting,Embedding,Web page,Pattern recognition,Computer science,3d shapes,Filter (signal processing),Artificial intelligence,Prior probability,Modal
Conference
ISSN
ISBN
Citations 
2378-3826
978-1-5386-2611-5
2
PageRank 
References 
Authors
0.39
14
5
Name
Order
Citations
PageRank
Lin Shao1123.33
Angel Chang2134058.19
Hao Su37343302.07
Manolis Savva457825.50
Leonidas J. Guibas5130841262.73