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» Learning Models for Object Recognition
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157
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CVPR
2012
IEEE
13 years 6 months ago
Estimating the aspect layout of object categories
In this work we seek to move away from the traditional paradigm for 2D object recognition whereby objects are identified in the image as 2D bounding boxes. We focus instead on: i...
Yu Xiang, Silvio Savarese
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
15 years 8 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
137
Voted
JIRS
2007
116views more  JIRS 2007»
15 years 3 months ago
Recognition of Human Motion From Qualitative Normalised Templates
Abstract This paper proposes a Qualitative Normalised Templates (QNTs) framework for solving the human motion classification problem. In contrast to other human motion classifica...
Chee Seng Chan, Honghai Liu, David J. Brown
98
Voted
ICASSP
2009
IEEE
15 years 7 months ago
Learning to maximize signal-to-noise ratio for reverberant speech segregation
Monaural speech segregation in reverberant environments is a very difficult problem. We develop a supervised learning approach by proposing an objective function that directly rel...
Zhaozhang Jin, DeLiang Wang
ECCV
2010
Springer
15 years 8 months ago
What, Where & How Many? Combining Object Detectors and CRFs
Abstract. Computer vision algorithms for individual tasks such as object recognition, detection and segmentation have shown impressive results in the recent past. The next challeng...