WebWe propose to learn a spherical convolutional network that translates a planar CNN to process 360 {\deg} imagery directly in its equirectangular projection. Our approach learns to reproduce the flat filter outputs on 360 {\deg} data, sensitive to the varying distortion effects across the viewing sphere. WebOct 7, 2024 · Abstract: Deep Learning techniques like Convolutional Neural Networks (CNN) are getting popular for image classification with broad usage spanning across automotive, industrial, medicine, robotics etc. Typical CNN network consists of multiple layers of 2D convolutions, non-linearity, spatial pooling and fully connected layer, with 2D convolutions …
[2202.04942] Spherical Transformer - arXiv.org
WebOur code is available at https: //github.com/deepsphere. 1 INTRODUCTION Spherical data is found in many applications (figure 1). Planetary data (such as meteorological or geological measurements) and brain activity are example of intrinsically spherical data. WebDec 30, 2024 · DeepSphere: a graph-based spherical CNN. Designing a convolution for a spherical neural network requires a delicate tradeoff between efficiency and rotation … it\\u0027s lightning mcqueen
3D object classification and retrieval with Spherical CNNs
WebJan 30, 2024 · We propose a definition for the spherical cross-correlation that is both expressive and rotation-equivariant. The spherical correlation satisfies a generalized Fourier theorem, which allows us to compute it efficiently using a generalized (non-commutative) Fast Fourier Transform (FFT) algorithm. WebSpherical data can be seen as a continuous function that is sampled at discrete locations. As it is impossible to construct a regular discretization of the sphere, there is no perfect … WebMichaël Defferrard. @mdeff. Research on machine learning and graphs. Open science, open source, open data. Educator and mentor. Brass band musician. I am a Machine Learning researcher, currently pursuing a PhD at the École Polytechnique Fédérale de Lausanne (EPFL) with Prof. Pierre Vandergheynst . My main research interest is the modeling ... netball water bottle