Paper Info
Title
Are Cars Just 3D Boxes? Jointly Estimating the 3D Shape of Multiple Objects
Abstract
Current systems for scene understanding typically represent objects as 2D or 3D bounding boxes. While these representations have proven robust in a variety of applications, they provide only coarse approximations to the true 2D and 3D extent of objects. As a result, object-object interactions, such as occlusions or ground-plane contact, can be represented only superficially. In this paper, we approach the problem of scene understanding from the perspective of 3D shape modeling, and design a 3D scene representation that reasons jointly about the 3D shape of multiple objects. This representation allows to express 3D geometry and occlusion on the fine detail level of individual vertices of 3D wireframe models, and makes it possible to treat dependencies between objects, such as occlusion reasoning, in a deterministic way. In our experiments, we demonstrate the benefit of jointly estimating the 3D shape of multiple objects in a scene over working with coarse boxes, on the recently proposed KITTI dataset of realistic street scenes.
Year
DOI
Venue
2014
10.1109/CVPR.2014.470
Computer Vision and Pattern Recognition
Keywords
Field
DocType
image representation,object detection,shape recognition,3D geometry,3D scene representation,3D shape modeling,3D wireframe models,ground-plane contact,multiple objects 3D shape estimation,object-object interactions,occlusion reasoning,realistic street scenes,3D object recognition,Scene understanding
Computer vision,3d geometry,Vertex (geometry),Computer science,Artificial intelligence,Bounding overwatch
Conference
ISSN
Citations 
PageRank 
1063-6919
19
0.62
References 
Authors
33
3
Name
Order
Citations
PageRank
Muhammad Zeeshan Zia1190.62
Michael Stark273726.80
Konrad Schindler32860133.41