Per-Erik Forssén
Biträdande professor
Mina forskningsintressen är visuell perception och perceptuell inlärning för robotar. Aktuell forskning har inriktning mot osäkerhetsrepresentation, aktionskopplat seende och tidskontinuerliga modeller för 3D-rörelse.
Vänligen besök den engelska versionen för mer information.
Utvalda publikationer
Felix Järemo-Lawin, Per-Erik Forssén, Hannes Ovrén
(2016)
Computer Vision – ECCV 2016 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part IV
, s.170-185
Vidare till DOI
Johan Hedborg, Per-Erik Forssén, Michael Felsberg, Erik Ringaby
(2012)
Erik Ringaby, Per-Erik Forssén
(2012)
International Journal of Computer Vision
, Vol.96
, s.335-352
Vidare till DOI
Fler publikationer
Ludvig Dillén, Per-Erik Forssén, Johan Edstedt, FACT: Multinomial Misalignment Classification for Point Cloud Registration (2025) 
https://arxiv.org/abs/2504.06627
Ziliang Xiong, Shipeng Liu, Nathaniel Helgesen, Joakim Johnander, Per-Erik Forssen, CATPlan: Loss-based Collision Prediction in End-to-End Autonomous Driving (2025) https://arxiv.org/abs/2503.07425
Emmanuele Barberi, Filippo Cucinotta, Per-Erik Forssén, Marcello Raffaele, Fabio Salmeri, 
A Differential Entropy-Based Method for Reverse Engineering Quality Assessment, DESIGN TOOLS AND METHODS IN INDUSTRIAL ENGINEERING III, VOL 2, ADM 2023, Lecture Notes in Mechanical Engineering, pp. 451-458, SPRINGER INTERNATIONAL PUBLISHING AG (2024) 
https://doi.org/10.1007/978-3-031-58094-9_50
Simon Kristoffersson Lind, Ziliang Xiong, Per-Erik Forssén, Volker Kruger, Uncertainty quantification metrics for deep regression, Pattern Recognition Letters 186:91-97 (2024) https://doi.org/10.1016/j.patrec.2024.09.011 https://arxiv.org/abs/2405.04278
Ziliang Xiong, Arvi Jonnarth, Abdelrahman Eldesokey, Joakim Johnander, Bastian Wandt, Per-Erik Forssén, Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 3471-3480, IEEE (2024) https://doi.org/10.1109/cvprw63382.2024.00351
