Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Ganesh Sundaramoorthi"'
Publikováno v:
SIAM Journal on Imaging Sciences. 15:324-366
Publikováno v:
SIAM J Imaging Sci
Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient based parameter estimation in scenarios where second-order optimization strategies are either inappli
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
In this paper we present a novel loss function, called class-agnostic segmentation (CAS) loss. With CAS loss the class descriptors are learned during training of the network. We don't require to define the label of a class a-priori, rather the CAS lo
We consider the problem of filling in missing spatio-temporal regions of a video. We provide a novel flow-based solution by introducing a generative model of images in relation to the scene (without missing regions) and mappings from the scene to ima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fdf08d26b2d244a59a07cad5a99c5b7
http://arxiv.org/abs/2108.12845
http://arxiv.org/abs/2108.12845
Publikováno v:
J Math Imaging Vis
We further develop a new framework, called PDE acceleration, by applying it to calculus of variation problems defined for general functions on $$\mathbb {R}^n$$, obtaining efficient numerical algorithms to solve the resulting class of optimization pr
Autor:
Marei Algarni, Ganesh Sundaramoorthi
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 41:726-739
We present SurfCut , an algorithm for extracting a smooth, simple surface with an unknown 3D curve boundary from a noisy 3D image and a seed point. Our method is built on the novel observation that ridge curves of the Euclidean length of minimal path
Publikováno v:
CVPR
We introduce two criteria to regularize the optimization involved in learning a classifier in a domain where no annotated data are available, leveraging annotated data in a different domain, a problem known as unsupervised domain adaptation. We focus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8484ff8f9a22de7e305842dec390bc48
http://arxiv.org/abs/2004.04923
http://arxiv.org/abs/2004.04923
Publikováno v:
CVPR
Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inappli
Autor:
Poornima Madhavan, Markus Hadwiger, Ganesh Sundaramoorthi, Ali Reza Behzad, Mohamed Ben-Romdhane, Suzana Pereira Nunes
Publikováno v:
Industrial & Engineering Chemistry Research. 55:3689-3695
Ultrafiltration asymmetric porous membranes were imaged by two microscopy methods, which allow 3D reconstruction: focused ion beam and serial block face scanning electron microscopy. A new algorithm was proposed to evaluate porosity and average pore
Autor:
Naeemullah Khan, Ganesh Sundaramoorthi
Publikováno v:
CVPR
We address the problem of texture segmentation by grouping dense pixel-wise descriptors. We introduce and construct learned Shape-Tailored Descriptors that aggregate image statistics only within regions of interest to avoid mixing statistics of diffe