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Ameesh Makadia

I am currently a Research Scientist with Google in New York City. Before joining Google Research in NYC, I was a graduate student in the GRASP Lab. In the Computer and Information Science. Working with Dr. Kostas Daniilidis. The areas of research I have worked in include motion estimation, structure-from-motion, and 3D registration and matching. Our research focused on correspondenceless techniques and the application of harmonic analysis theory to various vision problems.

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AMEESH MAKADIA

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AMEESH MAKADIA

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Ameesh Makadia | ameeshmakadia.com Reviews
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I am currently a Research Scientist with Google in New York City. Before joining Google Research in NYC, I was a graduate student in the GRASP Lab. In the Computer and Information Science. Working with Dr. Kostas Daniilidis. The areas of research I have worked in include motion estimation, structure-from-motion, and 3D registration and matching. Our research focused on correspondenceless techniques and the application of harmonic analysis theory to various vision problems.
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1 ameesh makadia
2 makadia@cis upenn edu
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Ameesh Makadia | ameeshmakadia.com Reviews

https://ameeshmakadia.com

I am currently a Research Scientist with Google in New York City. Before joining Google Research in NYC, I was a graduate student in the GRASP Lab. In the Computer and Information Science. Working with Dr. Kostas Daniilidis. The areas of research I have worked in include motion estimation, structure-from-motion, and 3D registration and matching. Our research focused on correspondenceless techniques and the application of harmonic analysis theory to various vision problems.

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Background

http://www.ameeshmakadia.com/background.html

Background before 2001 ( Back to main page. PhD in Computer and Information Science (2007). MS in Computer and Information Science (2003). BS in Computer Science and Mathematics (May, 2001). Intern (Summer 1998, 1999).

2

Publications

http://www.ameeshmakadia.com/publications.html

Selected Publications ( Back to main page. Learning 3D Part Detection from Sparsely Labeled Data. Ameesh Makadia and Mehmet Yumer. To appear in 3DV. Tokyo, December 2014. Co-Segmentation of Textured 3D Shapes with Sparse Annotations. Mehmet Yumer, Won Chun, and Ameesh Makadia. IEEE Conference on Computer Vision and Pattern Recognition. Columbus, June 2014. Label Partitioning For Sublinear Ranking. Jason Weston, Ameesh Makadia, and Hector Yee. International Conference on Machine Learning. Miami, May 2009.

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I am currently a Research Scientist with Google in New York City. Before joining Google Research in NYC, I was a graduate student in the GRASP Lab. In the Computer and Information Science. Working with Dr. Kostas Daniilidis. The areas of research I have worked in include motion estimation, structure-from-motion, and 3D registration and matching. Our research focused on correspondenceless techniques and the application of harmonic analysis theory to various vision problems.

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