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Tomasi–Kanade factorization

Known as: Tomasi, Tomasi-Kanade Factorization 
The Tomasi–Kanade factorization is the seminal work by Carlo Tomasi and Takeo Kanade in the early 1990s. It charted out an elegant and simple… Expand
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Papers overview

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Highly Cited
2015
Highly Cited
2015
We present the Word Mover's Distance (WMD), a novel distance function between text documents. Our work is based on recent results… Expand
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Highly Cited
2014
Highly Cited
2014
This paper presents a novel structure-preserving image decomposition operator called bilateral texture filter. As a simple… Expand
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Highly Cited
2012
Highly Cited
2012
This paper introduces a video representation based on dense trajectories and motion boundary descriptors. Trajectories capture… Expand
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Highly Cited
2011
Highly Cited
2011
Applications for real-time visual tracking can be found in many areas, including visual odometry and augmented reality. Interest… Expand
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Highly Cited
2009
Highly Cited
2009
We present a new algorithm for a robust family of Earth Mover's Distances - EMDs with thresholded ground distances. The algorithm… Expand
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Highly Cited
2005
Highly Cited
2005
Publisher Summary This chapter focuses on the new developments in electronic structure theory during the past decade. These… Expand
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Highly Cited
2003
Highly Cited
2003
We present a new, single-pass nonlinear filter for edge-preserving smoothing and visual detail removal for N dimensional signals… Expand
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Highly Cited
1999
Highly Cited
1999
The increasing amount of information available in today''s world raises the need to retrieve relevant data efficiently. Unlike… Expand
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Highly Cited
1996
Highly Cited
1996
  • Bill Triggs
  • Proceedings CVPR IEEE Computer Society Conference…
  • 1996
  • Corpus ID: 14791448
This paper describes a family of factorization-based algorithms that recover 3D projective structure and motion from multiple… Expand
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Highly Cited
1993
Highly Cited
1993
Abstract The oft-observed inverse relationship between farm size and productivity has elicited several explanations having… Expand
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