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» Learning Hierarchical Models of Scenes, Objects, and Parts
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CVPR
2012
IEEE
13 years 4 days ago
Learning hierarchical similarity metrics
Categories in multi-class data are often part of an underlying semantic taxonomy. Recent work in object classification has found interesting ways to use this taxonomy structure t...
Nakul Verma, Dhruv Mahajan, Sundararajan Sellamani...
PAMI
2012
13 years 5 days ago
Recognizing Human-Object Interactions in Still Images by Modeling the Mutual Context of Objects and Human Poses
—Detecting objects in cluttered scenes and estimating articulated human body parts from 2D images are two challenging problems in computer vision. The difficulty is particularly...
Bangpeng Yao, Fei-Fei Li
ACCV
2006
Springer
15 years 3 months ago
Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes
Abstract. In this paper we give a new model for foreground-background-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly...
Csaba Benedek, Tamás Szirányi
ICCV
2005
IEEE
15 years 11 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
121
Voted
NIPS
1998
14 years 11 months ago
Learning to Estimate Scenes from Images
We seek the scene interpretation that best explains image data. For example, we may want to infer the projected velocities (scene) which best explain two consecutive image frames ...
William T. Freeman, Egon C. Pasztor