Måns Larsson
TitleCited byYear
Conditional random fields meet deep neural networks for semantic segmentation: Combining probabilistic graphical models with deep learning for structured prediction
A Arnab, S Zheng, S Jayasumana, B Romera-Paredes, M Larsson, ...
IEEE Signal Processing Magazine 35 (1), 37-52, 2018
442018
A projected gradient descent method for CRF inference allowing end-to-end training of arbitrary pairwise potentials
M Larsson, A Arnab, F Kahl, S Zheng, P Torr
International Workshop on Energy Minimization Methods in Computer Vision and …, 2017
17*2017
Robust abdominal organ segmentation using regional convolutional neural networks
M Larsson, Y Zhang, F Kahl
Applied Soft Computing 70, 465-471, 2018
122018
A cross-season correspondence dataset for robust semantic segmentation
M Larsson, E Stenborg, L Hammarstrand, M Pollefeys, T Sattler, F Kahl
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
82019
Revisiting Deep Structured Models for Pixel-Level Labeling with Gradient-Based Inference
M Larsson, A Arnab, S Zheng, P Torr, F Kahl
SIAM Journal on Imaging Sciences 11 (4), 2610-2628, 2018
52018
Max-margin learning of deep structured models for semantic segmentation
M Larsson, J Alvén, F Kahl
Scandinavian Conference on Image Analysis, 28-40, 2017
42017
DeepSeg: Abdominal Organ Segmentation Using Deep Convolutional Neural Networks
M Larsson, Y Zhang, F Kahl
Swedish Symposium on Image Analysis 2016, 2016
42016
Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization
M Larsson, E Stenborg, C Toft, L Hammarstrand, T Sattler, F Kahl
Proceedings of the IEEE International Conference on Computer Vision, 31-41, 2019
12019
Automated construction of statistical deformation models for non-rigid registrations of the pericardium and hippocampus
M LARSSON
Master’s thesis, Chalmers University of Technology, 2015
12015
Estimering av snödjup genom analys av flervägsreflekterade GPS-signaler
M Larsson, J Nordevall, R Sirefelt, E Staf
Chalmers University of Technology, 2012
12012
End-to-End Learning of Deep Structured Models for Semantic Segmentation (Licentiate thesis)
M Larsson
https://research.chalmers.se/en/publication/500735, 2018
2018
Image segmentation and convolutional neural networks as tools for indoor scene understanding
A Liberda, A Lilja, B Langborn, J Lindström, F Kahl, M Larsson
2016
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