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» Learning Generic Prior Models for Visual Computation
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CVPR
2011
IEEE
14 years 7 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
AIHC
2007
Springer
15 years 6 months ago
Audio-Visual Spontaneous Emotion Recognition
Automatic multimodal recognition of spontaneous emotional expressions is a largely unexplored and challenging problem. In this paper, we explore audio-visual emotion recognition in...
Zhihong Zeng, Yuxiao Hu, Glenn I. Roisman, Zhen We...
AINA
2009
IEEE
15 years 6 months ago
Learning to Extract Content from News Webpages
We consider the problem of content extraction from online news webpages. To explore to what extent the syntactic markup and the visual structure of a webpage facilitate the extrac...
Alex Spengler, Patrick Gallinari
CVPR
2009
IEEE
1453views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Learning Photometric Invariance From Diversified Color Model Ensembles
Color is a powerful visual cue for many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the i...
Jose M. Alvarez, Theo Gevers, Antonio M. Lopez
ECCV
2008
Springer
16 years 1 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...