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» Learning Generic Prior Models for Visual Computation
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CVPR
2008
IEEE
15 years 11 months ago
Unsupervised discovery of visual object class hierarchies
Objects in the world can be arranged into a hierarchy based on their semantic meaning (e.g. organism ? animal ? feline ? cat). What about defining a hierarchy based on the visual ...
Josef Sivic, Bryan C. Russell, Andrew Zisserman, W...
CVPR
2006
IEEE
15 years 11 months ago
Noise Estimation from a Single Image
In order to work well, many computer vision algorithms require that their parameters be adjusted according to the image noise level, making it an important quantity to estimate. W...
Ce Liu, William T. Freeman, Richard Szeliski, Sing...
PSIVT
2009
Springer
139views Multimedia» more  PSIVT 2009»
15 years 4 months ago
Recognizing Multiple Objects via Regression Incorporating the Co-occurrence of Categories
Abstract. Most previous methods for generic object recognition explicitly or implicitly assume that an image contains objects from a single category, although objects from multiple...
Takahiro Okabe, Yuhi Kondo, Kris M. Kitani, Yoichi...
ACIVS
2008
Springer
15 years 4 months ago
Foliage Recognition Based on Local Edge Information
In many real-world object recognition applications, texture plays a very important role. Much research has gone into texture-based segmentation methods, which focus on finding the...
David Van Hamme, Peter Veelaert, Wilfried Philips,...
CVPR
2010
IEEE
15 years 3 months ago
Free-Form Mesh Tracking : a Patch-Based Approach
In this paper, we consider the problem of tracking nonrigid surfaces and propose a generic data-driven mesh deformation framework. In contrast to methods using strong prior models...
Cedric Cagniart, Edmond Boyer, Slobodan Ilic