Image morphing in deep feature spaces: theory and applications

DOI10.1007/s10851-020-00974-5OpenAlexW3042581250MaRDI QIDQ2031755

Alexander Effland, Erich Kobler, Marko Rajković, Thomas Pock, Martin Rumpf

Publication date: 14 June 2021

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.12672

zbMATH Keywords

convolutional neural networksvariational time discretizationimage morphingmosco convergencemetamorphosis model

Mathematics Subject Classification ID

Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Stability and convergence of numerical methods for ordinary differential equations (65L20) Geodesics in global differential geometry (53C22) Special approximation methods (nonlinear Galerkin, etc.) for infinite-dimensional dissipative dynamical systems (37L65) Discrete approximations in optimal control (49M25) Computer science (68-XX) Information and communication theory, circuits (94-XX)

Related Items

Splines for image metamorphosis, A singular Riemannian geometry approach to deep neural networks. II: Reconstruction of 1-D equivalence classes

Uses Software

• LDDMM
• ImageNet
• AlexNet

Cites Work

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