Titlebook: Computer Vision – ECCV 2012; 12th European Confer Andrew Fitzgibbon,Svetlana Lazebnik,Cordelia Schmi Conference proceedings 2012 Springer-V

得意人

Facial Action Transfer with Personalized Bilinear Regressiongames, and privacy protection. The goal of FAT is to “clone” the facial actions from the videos of one person (source) to another person (target). In this paper, we will assume that we have a video of the source person but only one frontal image of the target person. Most successful methods for FAT

MOTTO

多样

Hirsutism

口音在加重

On Learning Higher-Order Consistency Potentials for Multi-class Pixel Labelingmited by their inability to capture higher-order correlations. Recently proposed higher-order models are showing superior performance to their pairwise counterparts. In this paper, we derive two variants of the higher-order lower linear envelop model and show how to perform tractable move-making inf

GOAD

Surgeon

Learning Class-to-Image Distance via Large Margin and L1-Norm Regularization problem, where an image may contain several regions belonging to different classes, this distance may not work well since it cannot discriminate local features from different regions in the test image and all local features have to be counted in the I2C distance calculation. In this paper, we propo

指耕作

Taxonomic Multi-class Prediction and Person Layout Using Efficient Structured Rankingied increases. Often objects might have some sort of structure such as a taxonomy in which the mis-classification score for object classes close by, using tree distance within the taxonomy, should be less than for those far apart. This is an example of multi-class classification in which the loss fu

脾气暴躁的人

Robust Point Matching Revisited: A Concave Optimization Approachhe global optimality of the solution and tends to align the centers of two point sets. Second, deformation needs to be regularized to avoid the generation of undesirable results. To address these problems, in this paper we first show that the energy function of RPM can be reduced to a concave functi

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