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151
Voted
CVPR
2009
IEEE
16 years 10 months ago
Linear Embeddings in Non-Rigid Structure From Motion
This paper proposes a method to recover the embedding of the possible shapes assumed by a deforming nonrigid object by comparing triplets of frames from an orthographic video se...
Vincent Rabaud (University of California, San Dieg...
ICCV
2007
IEEE
16 years 5 months ago
Embedded Profile Hidden Markov Models for Shape Analysis
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
134
Voted
ECCV
2008
Springer
16 years 5 months ago
Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
This paper improves recent methods for large scale image search. State-of-the-art methods build on the bag-of-features image representation. We, first, analyze bag-of-features in t...
Herve Jegou, Matthijs Douze, Cordelia Schmid
113
Voted
ICPR
2008
IEEE
15 years 10 months ago
Face super-resolution using 8-connected Markov Random Fields with embedded prior
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...
127
Voted
CVPR
2010
IEEE
15 years 7 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu