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» Deriving Intrinsic Images from Image Sequences
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SCIA
2007
Springer
14 years 4 months ago
Pseudo-real Image Sequence Generator for Optical Flow Computations
Abstract. The availability of ground-truth flow field is crucial for quantitative evaluation of any optical flow computation method. The fidelity of test data is also important...
Vladimír Ulman, Jan Hubený
CVPR
1997
IEEE
15 years 4 days ago
Learning Parameterized Models of Image Motion
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
ISBI
2002
IEEE
14 years 10 months ago
On the effectiveness of doubly adaptive estimation for dynamic MRI sequence acquisitions
We present experimentally-acquired MR image sequence reconstruction results and a review of the recently proposed doubly adaptive temporal update method (DATUM) for the acquisitio...
William Scott Hoge, Lawrence P. Panych, Dana H. Br...
NECO
2008
114views more  NECO 2008»
13 years 10 months ago
A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
Cornelius Weber, Jochen Triesch
CVPR
2009
IEEE
14 years 4 months ago
Recovering Specular Surfaces Using Curved Line Images
We present a new shape-from-distortion framework for recovering specular (reflective/refractive) surfaces. While most existing approaches rely on accurate correspondences between 2...
Yuanyuan Ding, Jingyi Yu, Peter Sturm