1 citations · 1 across the 6 of their papers we have counts for
8 papers
GeoBlur: Epipolar Geometry Estimation from a Single Motion-Blurred Image
Bao-Long Tran, Per-Erik Forssén, Cuong Le +1
Relative camera pose geometry, formulated via fundamental matrix estimation, is a challenging problem in many robotics and VR/AR applications. These applications occasionally conta…
Collision Risk Estimation via Loss Prediction in End-to-End Autonomous Driving
Ziliang Xiong, Shipeng Liu, Nathaniel Helgesen +3
Collision risk estimation and avoidance play central roles in the safety of autonomous driving (AD) systems. Recently emerged end-to-end AD systems gain collision avoidance ability…
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks
Ziliang Xiong, Arvi Jonnarth, Abdelrahman Eldesokey +3
Computer vision systems that are deployed in safety-critical applications need to quantify their output uncertainty. We study regression from images to parameter values and here it…
Registration Loss Learning for Deep Probabilistic Point Set Registration
Felix Järemo Lawin, Per-Erik Forssén
Probabilistic methods for point set registration have interesting theoretical properties, such as linear complexity in the number of used points, and they easily generalize to join…
Trajectory Representation and Landmark Projection for Continuous-Time Structure from Motion
Hannes Ovrén, Per-Erik Forssén
This paper revisits the problem of continuous-time structure from motion, and introduces a number of extensions that improve convergence and efficiency. The formulation with a $\ma…
Spline Error Weighting for Robust Visual-Inertial Fusion
Hannes Ovrén, Per-Erik Forssén
In this paper we derive and test a probability-based weighting that can balance residuals of different types in spline fitting. In contrast to previous formulations, the proposed s…
Density Adaptive Point Set Registration
Felix Järemo Lawin, Martin Danelljan, Fahad Shahbaz Khan +2
Probabilistic methods for point set registration have demonstrated competitive results in recent years. These techniques estimate a probability distribution model of the point clou…
Efficient Multi-Frequency Phase Unwrapping using Kernel Density Estimation
Felix Järemo Lawin, Per-Erik Forssén, Hannes Ovrén
In this paper we introduce an efficient method to unwrap multi-frequency phase estimates for time-of-flight ranging. The algorithm generates multiple depth hypotheses and uses a sp…