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» The Dark Side of Object Learning: Learning Objects
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CVPR
2011
IEEE
13 years 5 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
3DOR
2010
13 years 4 months ago
Semantics-Driven Approach for Automatic Selection of Best Views of 3D Shapes
We introduce a new framework for the automatic selection of the best views of 3D models. The approach is based on the assumption that models belonging to the same class of shapes ...
Hamid Laga
ACCV
2010
Springer
13 years 4 months ago
Efficient Structured Support Vector Regression
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structu...
Ke Jia, Lei Wang, Nianjun Liu
CVPR
2011
IEEE
13 years 24 days ago
A Hierarchical Conditional Random Field Model for Labeling and Segmenting Images of Street Scenes
Simultaneously segmenting and labeling images is a fundamental problem in Computer Vision. In this paper, we introduce a hierarchical CRF model to deal with the problem of labelin...
Qixing Huang, Mei Han, Bo Wu, Sergey Ioffe
CVPR
2011
IEEE
13 years 24 days ago
Robust Tracking Using Local Sparse Appearance Model and K-Selection
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Baiyang Liu, junzhou Huang, Casimir Kulikowski, Li...