Mårten Wadenbäck
Associate Professor, Docent
Publications
Mårten Wadenbäck, Marcus Valtonen Örnhag, Johan Edstedt, Radially Distorted Homographies, Revisited (2025) 
https://arxiv.org/abs/2508.21190
Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg, DaD: Distilled Reinforcement Learning for Diverse Keypoint Detection (2025) https://arxiv.org/abs/2503.07347
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 https://doi.org/10.48550/arXiv.2308.08479
Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg, RoMa: Robust Dense Feature Matching, 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Conference on Computer Vision and Pattern Recognition (CVPR), pp. 19790-19800, Institute of Electrical and Electronics Engineers (IEEE) (2024) https://doi.org/10.1109/CVPR52733.2024.01871 https://doi.org/10.48550/arXiv.2305.15404
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
