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184
Voted
CVPR
2008
IEEE
16 years 9 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
223
Voted
CVPR
2008
IEEE
16 years 9 months ago
Structure-perceptron learning of a hierarchical log-linear model
In this paper, we address the problems of deformable object matching (alignment) and segmentation with cluttered background. We propose a novel hierarchical log-linear model (HLLM...
Long Zhu, Yuanhao Chen, Xingyao Ye, Alan L. Yuille
217
Voted
CVPR
2008
IEEE
16 years 9 months ago
Scene classification with low-dimensional semantic spaces and weak supervision
A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "t...
Nikhil Rasiwasia, Nuno Vasconcelos
ICCV
2007
IEEE
16 years 9 months ago
A Divide-and-Conquer Approach to 3D Object Reconstruction from Line Drawings
3D object reconstruction from a single 2D line drawing is an important problem in both computer vision and graphics. Many methods have been put forward to solve this problem, but ...
Yu Chen, Jianzhuang Liu, Xiaoou Tang
222
Voted
ICCV
1999
IEEE
16 years 9 months ago
Object Recognition from Local Scale-Invariant Features
Proc. of the International Conference on Computer Vision, Corfu (Sept. 1999) An object recognition system has been developed that uses a new class of local image features. The fea...
David G. Lowe