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» Learning the parts of objects by auto-association
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AIRS
2010
Springer
13 years 5 months ago
Learning to Rank with Supplementary Data
This paper is concerned with a new task of ranking, referred to as "supplementary data assisted ranking", or "supplementary ranking" for short. Different from c...
Wenkui Ding, Tao Qin, Xu-Dong Zhang
NIPS
2001
13 years 9 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
CVPR
2007
IEEE
14 years 2 months ago
Unsupervised Learning of Hierarchical Semantics of Objects (hSOs)
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Devi Parikh, Tsuhan Chen
ICCV
2003
IEEE
14 years 9 months ago
A Multi-scale Generative Model for Animate Shapes and Parts
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...
Aleksandr Dubinskiy, Song Chun Zhu
CLOR
2006
13 years 11 months ago
Visual Classification by a Hierarchy of Extended Fragments
The chapter describes visual classification by a hierarchy of semantic fragments. In fragment-based classification, objects within a class are represented by common sub-structures ...
Shimon Ullman, Boris Epshtein