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ICCV
2005
IEEE
14 years 6 months ago
Learning Non-Negative Sparse Image Codes by Convex Programming
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Christoph Schnörr, Matthias Heiler
ICCV
2005
IEEE
14 years 6 months ago
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization
We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the pas...
Tamir Hazan, Simon Polak, Amnon Shashua
CORR
2002
Springer
180views Education» more  CORR 2002»
13 years 4 months ago
Non-negative sparse coding
Abstract. Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this...
Patrik O. Hoyer
CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 4 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
ICIP
2008
IEEE
14 years 6 months ago
Face hallucination VIA sparse coding
In this paper, we address the problem of hallucinating a high resolution face given a low resolution input face. The problem is approached through sparse coding. To exploit the fa...
Jianchao Yang, Hao Tang, Yi Ma, Thomas S. Huang