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» The Dark Side of Object Learning: Learning Objects
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CVPR
2010
IEEE
14 years 2 months ago
Object Recognition as Ranking Holistic Figure-Ground Hypotheses
We present an approach to visual object-class recognition and segmentation based on a pipeline that combines multiple, holistic figure-ground hypotheses generated in a bottom-up,...
Fuxin Li, JoãCarreira, Cristian Sminchisescu
ICIAP
2009
ACM
14 years 1 months ago
Applying Visual Object Categorization and Memory Colors for Automatic Color Constancy
This paper presents a framework for using high-level visual information to enhance the performance of automatic color constancy algorithms. The approach is based on recognizing spe...
Esa Rahtu, Jarno Nikkanen, Juho Kannala, Leena Lep...
CVPR
2008
IEEE
13 years 11 months ago
Optimizing discrimination-efficiency tradeoff in integrating heterogeneous local features for object detection
A large variety of image features has been invented for detection of objects of a known class. We propose a framework to optimize the discrimination-efficiency tradeoff in integra...
Bo Wu, Ram Nevatia
VRST
1997
ACM
14 years 1 months ago
Image-based view synthesis by combining trilinear tensors and learning techniques
We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to sy...
Shai Avidan, Theodoros Evgeniou, Amnon Shashua, To...
JMLR
2012
11 years 11 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee