Search Results for author: Michael Kazhdan

Found 7 papers, 3 papers with code

Möbius Convolutions for Spherical CNNs

1 code implementation28 Jan 2022 Thomas W. Mitchel, Noam Aigerman, Vladimir G. Kim, Michael Kazhdan

M\"obius transformations play an important role in both geometry and spherical image processing - they are the group of conformal automorphisms of 2D surfaces and the spherical equivalent of homographies.

Descriptive Image Segmentation +1

Field Convolutions for Surface CNNs

1 code implementation ICCV 2021 Thomas W. Mitchel, Vladimir G. Kim, Michael Kazhdan

We present a novel surface convolution operator acting on vector fields that is based on a simple observation: instead of combining neighboring features with respect to a single coordinate parameterization defined at a given point, we have every neighbor describe the position of the point within its own coordinate frame.

Descriptive

Skin Lesion Correspondence Localization in Total Body Photography

1 code implementation18 Jul 2023 Wei-Lun Huang, Davood Tashayyod, Jun Kang, Amir Gandjbakhche, Michael Kazhdan, Mehran Armand

Longitudinal tracking of skin lesions - finding correspondence, changes in morphology, and texture - is beneficial to the early detection of melanoma.

Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes

no code implementations16 Apr 2014 Ayushi Sinha, William Gray Roncal, Narayanan Kasthuri, Ming Chuang, Priya Manavalan, Dean M. Kleissas, Joshua T. Vogelstein, R. Jacob Vogelstein, Randal Burns, Jeff W. Lichtman, Michael Kazhdan

The contribution of this work is the introduction of a straightforward and robust pipeline which annotates axoplasmic reticula with high precision, contributing towards advancements in automatic feature annotations in neural EM data.

Efficient Spatially Adaptive Convolution and Correlation

no code implementations23 Jun 2020 Thomas W. Mitchel, Benedict Brown, David Koller, Tim Weyrich, Szymon Rusinkiewicz, Michael Kazhdan

Fast methods for convolution and correlation underlie a variety of applications in computer vision and graphics, including efficient filtering, analysis, and simulation.

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