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» RGB-(D) scene labeling: Features and algorithms
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ECCV
2010
Springer
13 years 5 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang

Publication
234views
11 years 8 months ago
Road Scene Understanding from a Single Image
Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes ...
Jose M. Alvarez, Theo Gevers, Yann LeCun, Antonio ...
ICCV
2009
IEEE
14 years 9 months ago
Scene Shape Priors for Superpixel Segmentation
Unsupervised over-segmentation of an image into superpixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feat...
Alastair P. Moore, Simon J. D. Prince, Jonathan Wa...
CVPR
2008
IEEE
14 years 6 months ago
Scene classification with low-dimensional semantic spaces and weak supervision
A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "t...
Nikhil Rasiwasia, Nuno Vasconcelos
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 6 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang