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» Pruning Training Sets for Learning of Object Categories
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ICCV
2011
IEEE
12 years 9 months ago
Actively Selecting Annotations Among Objects and Attributes
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
Adriana Kovashka, Sudheendra Vijayanarasimhan, Kri...
ECCV
2008
Springer
14 years 11 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
CIKM
2008
Springer
13 years 11 months ago
Ranking information resources in peer-to-peer text retrieval: an experimental study
This paper experimentally studies approaches to the problem of ranking information resources w.r.t. user queries in peer-to-peer information retrieval. In distributed environments...
Hans F. Witschel
ICIP
2008
IEEE
14 years 3 months ago
Level set tracking with dynamical shape priors
Dynamical shape priors are curical for level set-based nonrigid object tracking with noise, occlusions or background clutter. In this paper, we propose a level set tracking framew...
Xue Zhou, Xi Li, Weiming Hu
CVPR
2010
IEEE
14 years 2 months ago
Many-to-one Contour Matching for Describing and Discriminating Object Shape
We present an object recognition system that locates an object, identifies its parts, and segments out its contours. A key distinction of our approach is that we use long, salien...
Praveen Srinivasan, Qihui Zhu, Jianbo Shi