no code implementations • 29 Jun 2023 • Arvi Jonnarth, Jie Zhao, Michael Felsberg
Coverage path planning (CPP) is the problem of finding a path that covers the entire free space of a confined area, with applications ranging from robotic lawn mowing to search-and-rescue.
no code implementations • 1 Jun 2023 • Ziliang Xiong, Arvi Jonnarth, Abdelrahman Eldesokey, Joakim Johnander, Bastian Wandt, Per-Erik Forssen
Computer vision systems that are deployed in safety-critical applications need to quantify their output uncertainty.
1 code implementation • 5 Apr 2023 • Arvi Jonnarth, Yushan Zhang, Michael Felsberg
Our work is based on two techniques for improving CAMs; importance sampling, which is a substitute for GAP, and the feature similarity loss, which utilizes a heuristic that object contours almost always align with color edges in images.
1 code implementation • CVPR 2023 • Emanuel Sanchez Aimar, Arvi Jonnarth, Michael Felsberg, Marco Kuhlmann
We show how to properly define these distributions and combine the experts in order to achieve unbiased predictions, by proving that the ensemble is Fisher-consistent for minimizing the balanced error.
Long-tail Learning Long-tail Learning on CIFAR-10-LT (ρ=100) +1
1 code implementation • 23 Mar 2022 • Arvi Jonnarth, Michael Felsberg
Classification networks can be used to localize and segment objects in images by means of class activation maps (CAMs).
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation