Publication list

Recent preprints

Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg, RoMa: Robust Dense Feature Matching (2023)  https://arxiv.org/abs/2305.15404

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck, Andreas Robinson, Cuong Le, O\(n\) Learning Deep O(\(n\))-Equivariant Hyperspheres (2023)  https://arxiv.org/abs/2305.15613

Conference papers

Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg,  DeDoDe: Detect, Don’t Describe — Describe, Don’t Detect for Local Feature Matching, 2024 International Conference on 3D Vision (3DV), 2024 International Conference on 3D Vision (3DV), Institute of Electrical and Electronics Engineers (IEEE) (2024)  https://doi.org/10.1109/3dv62453.2024.00035

Johan Edstedt, Ioannis Athanasiadis, Mårten Wadenbäck, Michael Felsberg,  DKM: Dense Kernelized Feature Matching for Geometry Estimation, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Proceedings:IEEE Conference on Computer Vision and Pattern Recognition, pp. 17765-17775, IEEE Communications Society (2023)  https://doi.org/10.1109/cvpr52729.2023.01704  https://arxiv.org/abs/2202.00667

Marcus Valtonen Örnhag, Patrik Persson, Mårten Wadenbäck, Kalle Åström, Anders Heyden,  Trust Your IMU: Consequences of Ignoring the IMU Drift, Proceedings 2022 IEEE/CVF Conference on Computer Visionand Pattern Recognition Workshops, IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops, pp. 4467-4476, IEEE Computer Society (2022)  https://doi.org/10.1109/cvprw56347.2022.00493  https://arxiv.org/abs/2103.08286

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck,  Steerable 3D Spherical Neurons, Proceedings of the 39th International Conference on Machine Learning, Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvari, Gang Niu, Sivan Sabato (eds.), Proceedings of Machine Learning Research, pp. 15330-15339, PMLR (2022)  https://arxiv.org/abs/2106.13863

Marcus Valtonen Örnhag, Patrik Persson, Mårten Wadenbäck, Kalle Åström, Anders Heyden,  Efficient Real-Time Radial Distortion Correction for UAVs, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1750-1759 (2021)  https://doi.org/10.1109/WACV48630.2021.00179  https://arxiv.org/abs/2010.04203

Marcus Valtonen Örnhag, Patrik Persson, Mårten Wadenbäck, Kalle Åström, Anders Heyden,  Minimal Solvers for Indoor UAV Positioning, 2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), International Conference on Pattern Recognition, pp. 1136-1143, IEEE COMPUTER SOC (2021)  https://doi.org/10.1109/ICPR48806.2021.9412279  https://arxiv.org/abs/2003.07111

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck,  Embed Me If You Can: A Geometric Perceptron, Proceedings 2021 IEEE/CVF International Conference on Computer Vision ICCV 2021, IEEE International Conference on Computer Vision. Proceedings, pp. 1256-1264, Institute of Electrical and Electronics Engineers (IEEE) (2021)  https://doi.org/10.1109/iccv48922.2021.00131  https://arxiv.org/abs/2006.06507

Journal papers

Wojciech Chojnacki, Zygmunt L. Szpak, Mårten Wadenbäck,  The equivalence of two definitions of compatible homography matrices, Pattern Recognition Letters 135:38-43 (2020)  https://doi.org/10.1016/j.patrec.2020.03.033

Preprints

Pavlo Melnyk, Andreas Robinson, Michael Felsberg, Mårten Wadenbäck, TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis (2022)  https://arxiv.org/abs/2211.14456

Mårten Wadenbäck, A Result for Orthogonal Plus Rank-1 Matrices (2015)  https://arxiv.org/abs/1512.03715