Mårten Wadenbäck
Associate Professor, Docent
Publications
Mårten Wadenbäck, Marcus Valtonen Örnhag, Johan Edstedt, 
Radially Distorted Homographies, Revisited, 2026 International Conference on 3D Vision (3DV), 2026 International Conference on 3D Vision (3DV), pp. 52-62, Institute of Electrical and Electronics Engineers (IEEE) (2026) 
https://doi.org/10.1109/3dv69130.2026.00012 
https://arxiv.org/abs/2508.21190
David Nordström, Johan Edstedt, Georg Bökman, Jonathan Astermark, Anders Heyden, Viktor Larsson, Mårten Wadenbäck, Michael Felsberg, Fredrik Kahl, LoMa: Local Feature Matching Revisited, Computer Vision - ECCV 2026, Paolo Favaro, Zuzana Kukelova, Atsuto Maki, Anna Rohrbach, Konrad Schindler, Federico Tombari (eds.), Lecture Notes in Computer Science, pp. 637-655, Springer (2026) https://doi.org/10.1007/978-3-032-37026-6_35 https://arxiv.org/abs/2604.04931
Johan Edstedt, David Nordström, Yushan Zhang, Georg Bökman, Jonathan Astermark, Viktor Larsson, Anders Heyden, Fredrik Kahl, Mårten Wadenbäck, Michael Felsberg, RoMa V2: Harder Better Faster Denser Feature Matching, Computer Vision - ECCV 2026, Paolo Favaro, Zuzana Kukelova, Atsuto Maki, Anna Rohrbach, Konrad Schindler, Federico Tombari (eds.), Lecture Notes in Computer Science, pp. 664-682, Springer (2026) https://doi.org/10.1007/978-3-032-37225-3_36 https://arxiv.org/abs/2511.15706
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://arxiv.org/abs/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://arxiv.org/abs/2305.15404
