Title
Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation.
Abstract
This paper presents a method for learning an And-Or model to represent context and occlusion for car detection and viewpoint estimation. The learned And-Or model represents car-to-car context and occlusion configurations at three levels: (i) spatially-aligned cars, (ii) single car under different occlusion configurations, and (iii) a small number of parts. The And-Or model embeds a grammar for rep...
Year
DOI
Venue
2016
10.1109/TPAMI.2015.2497699
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keywords
DocType
Volume
Solid modeling,Context modeling,Automobiles,Context,Data models,Estimation,Design automation
Journal
38
Issue
ISSN
Citations 
9
0162-8828
9
PageRank 
References 
Authors
0.48
42
3
Name
Order
Citations
PageRank
Tianfu Wu133126.72
Bo Li2634.01
Song-Chun Zhu36580741.75