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Nagesh Adluru

7 accepted papers

2018

Efficient Relative Attribute Learning using Graph Neural Networks

ECCV 2018poster

A sizable body of work on relative attributes provides compelling evidence that relating pairs of images along a continuum of strength pertaining to a visual attribute yields significant improvements in a wide variety of tasks in vision. In this paper, we show how emerging ideas in graph neural netw…

2017

A Geometric Framework for Statistical Analysis of Trajectories With Distinct Temporal Spans

ICCV 2017poster

Analyzing data representing multifarious trajectories is central to the many fields in Science and Engineering; for example, trajectories representing a tennis serve, a gymnast's parallel bar routine, progression/remission of disease and so on. We present a novel geometric algorithm for performing s…

Cited by 8PDFScholar
2017

Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging

CVPR 2017poster

Statistical machine learning models that operate on manifold-valued data are being extensively studied in vision, motivated by applications in activity recognition, feature tracking and medical imaging. While non-parametric methods have been relatively well studied in the literature, efficient formu…

Cited by 34PDFScholar
2016

Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks

CVPR 2016poster

There is a great deal of interest in using large scale brain imaging studies to understand how brain connectivity evolves over time for an individual and how it varies over different levels/quantiles of cognitive function. To do so, one typically performs so-called tractography procedures on diffusi…

Cited by 9PDFScholar
2016

Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP)

CVPR 2016spotlight

A major goal of imaging studies such as the (ongoing) Human Connectome Project (HCP) is to characterize the structural network map of the human brain and identify its associations with covariates such as genotype, risk factors, and so on that correspond to an individual. But the set of image derived…

Cited by 8PDFScholar
2015

A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer

ICCV 2015poster

Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation. Few other linear algebra problems have a more mature set of numerical routines available and many computer vision libra…

Cited by 13PDFScholar
2015

Interpolation on the Manifold of K Component GMMs

ICCV 2015poster

Probability density functions (PDFs) are fundamental "objects" in mathematics with numerous applications in computer vision, machine learning and medical imaging. The feasibility of basic operations such as computing the distance between two PDFs and estimating a mean of a set of PDFs is a direct fu…

Cited by 6PDFScholar