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» Unsupervised Learning of Visual Feature Hierarchies
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CVPR
2012
IEEE
13 years 2 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
ICCV
2009
IEEE
1824views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Beyond the Euclidean distance: Creating effective visual codebooks using the histogram intersection kernel
Common visual codebook generation methods used in a Bag of Visual words model, e.g. k-means or Gaussian Mixture Model, use the Euclidean distance to cluster features into visual...
Jianxin Wu, James M. Rehg
CVPR
2008
IEEE
16 years 1 months ago
Discriminative learning of visual words for 3D human pose estimation
This paper addresses the problem of recovering 3D human pose from a single monocular image, using a discriminative bag-of-words approach. In previous work, the visual words are le...
Huazhong Ning, Wei Xu, Yihong Gong, Thomas S. Huan...
CVPR
2005
IEEE
16 years 1 months ago
Semi-Supervised Adapted HMMs for Unusual Event Detection
We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the applica...
Dong Zhang, Daniel Gatica-Perez, Samy Bengio, Iain...
DAGM
2005
Springer
15 years 5 months ago
Rapid Online Learning of Objects in a Biologically Motivated Recognition Architecture
We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...
Stephan Kirstein, Heiko Wersing, Edgar Körner