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» Kernel Methods for Implicit Surface Modeling
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CVPR
2012
IEEE
11 years 9 months ago
Pose pooling kernels for sub-category recognition
The ability to normalize pose based on super-category landmarks can significantly improve models of individual categories when training data are limited. Previous methods have co...
Ning Zhang, Ryan Farrell, Trevor Darrell
SIGGRAPH
1993
ACM
13 years 11 months ago
Interval methods for multi-point collisions between time-dependent curved surfaces
We present an efficient and robust algorithm for finding points of collision between time-dependent parametric and implicit surfaces. The algorithm detects simultaneous collisio...
John M. Snyder, Adam R. Woodbury, Kurt W. Fleische...
ICML
2006
IEEE
14 years 8 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
NIPS
2008
13 years 8 months ago
Robust Kernel Principal Component Analysis
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Minh Hoai Nguyen, Fernando De la Torre
ACCV
2010
Springer
13 years 2 months ago
Image-Based 3D Modeling via Cheeger Sets
We propose a novel variational formulation for generating 3D models of objects from a single view. Based on a few user scribbles in an image, the algorithm automatically extracts t...
Eno Töppe, Martin R. Oswald, Daniel Cremers, ...