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» Improved Diffuse Reflection Models for Computer Vision
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CVPR
2005
IEEE
15 years 8 months ago
The Distinctiveness, Detectability, and Robustness of Local Image Features
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...
Gustavo Carneiro, Allan D. Jepson
CVPR
2003
IEEE
16 years 4 months ago
Shedding Light on the Weather
Virtually all methods in image processing and computer vision, for removing weather effects from images, assume single scattering of light by particles in the atmosphere. In reali...
Srinivasa G. Narasimhan, Shree K. Nayar
126
Voted
JGTOOLS
2008
189views more  JGTOOLS 2008»
15 years 2 months ago
Subtractive Shadows: A Flexible Framework for Shadow Level of Detail
Abstract. We explore the implications of reversing the process of shadow computation for real-time applications that model complex reflectance and lighting (such as that specified ...
Christopher DeCoro, Szymon Rusinkiewicz
106
Voted
ICPR
2010
IEEE
15 years 9 days ago
Enhancing Web Page Classification via Local Co-training
Abstract--In this paper we propose a new multi-view semisupervised learning algorithm called Local Co-Training (LCT). The proposed algorithm employs a set of local models with vect...
Youtian Du, Xiaohong Guan, Zhongmin Cai
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 9 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)