Aditya Tatu

Orcid: 0000-0003-1851-7983

According to our database1, Aditya Tatu authored at least 15 papers between 2007 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2021
Interval-Based Least Squares for Uncertainty-Aware Learning in Human-Centric Multimedia Systems.
IEEE Trans. Neural Networks Learn. Syst., 2021

2019
Affine interpolation in a lie group framework.
ACM Trans. Graph., 2019

Signal processing on graphs: structure preserving maps.
IET Signal Process., 2019

2018
Analysis of Downsampling of DCT-Graphs.
Proceedings of the 2018 International Conference on Signal Processing and Communications (SPCOM), 2018

Lie Bodies Based Deformation Transfer.
Proceedings of the ICVGIP 2018: 11th Indian Conference on Computer Vision, 2018

Lie bodies based 3D shape morphing and interpolation.
Proceedings of the 15th ACM SIGGRAPH European Conference on Visual Media Production, 2018

2017
Estimating graph topology from sparse graph signals with an application to image denoising.
Proceedings of the 19th IEEE International Workshop on Multimedia Signal Processing, 2017

Downsampling on bipartite graphs: An algebraic perspective.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016
Tangled Splines.
CoRR, 2016

2015
Active Contour Models for Manifold Valued Image Segmentation.
J. Math. Imaging Vis., 2015

2014
A Novel Active Contour Model for Texture Segmentation.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

2011
Exploring the representation capabilities of the HOG descriptor.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

2010
On Restricting Planar Curve Evolution to Finite Dimensional Implicit Subspaces with Non-Euclidean Metric.
J. Math. Imaging Vis., 2010

2009
Bicycle chain shape models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009

2007
Curve Evolution in Subspaces.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2007


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