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Author Title [ Type(Asc)] Year
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Miscellaneous
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). Image Labeling by Assignment. http://arxiv.org/abs/1603.05285
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2017). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. http://arxiv.org/abs/1710.01493
Aström, F and Schnörr, C (2016). A Geometric Approach to Color Image Regularization. https://arxiv.org/abs/1605.05977
Journal Article
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211–238. Papers/Astroem2017.pdf
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317–1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669
Aström, F and Schnörr, C (2017). A Geometric Approach for Color Image Regularization. Comp. Vision Image Understanding. 165 43–59. https://doi.org/10.1016/j.cviu.2017.10.013
Conference Paper
Zern, A, Zisler, M, Aström, F, Petra, S and Schnörr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR
Savarino, F, Hühnerbein, R, Aström, F, Recknagel, J and Schnörr, C (2017). Numerical Integration of Riemannian Gradient Flows for Image Labeling. Proc. SSVM. Springer. 10302
Aström, F, Hühnerbein, R, Savarino, F, Recknagel, J and Schnörr, C (2017). MAP Image Labeling Using Wasserstein Messages and Geometric Assignment. Proc. SSVM. Springer. 10302
Zisler, M, Aström, F, Petra, S and Schnörr, C (2017). Image Reconstruction by Multilabel Propagation. Proc. SSVM. Springer. 10302
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). A Geometric Approach to Image Labeling. Proc. ECCV
Aström, F and Schnörr, C (2016). Double-Opponent Vectorial Total Variation. Proc. ECCV
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). The Assignment Manifold: A Smooth Model for Image Labeling. Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award)