2 code implementations • 20 Oct 2017 • Gabriel Eilertsen, Joel Kronander, Gyorgy Denes, Rafał K. Mantiuk, Jonas Unger
We demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and low-end cameras that use unknown camera response functions and post-processing.
no code implementations • 17 Oct 2017 • Apostolia Tsirikoglou, Joel Kronander, Magnus Wrenninge, Jonas Unger
We present an overview and evaluation of a new, systematic approach for generation of highly realistic, annotated synthetic data for training of deep neural networks in computer vision tasks.
no code implementations • 17 Nov 2015 • Johan Dahlin, Fredrik Lindsten, Joel Kronander, Thomas B. Schön
Pseudo-marginal Metropolis-Hastings (pmMH) is a powerful method for Bayesian inference in models where the posterior distribution is analytical intractable or computationally costly to evaluate directly.
no code implementations • 22 Aug 2013 • Joel Kronander, Stefan Gustavson, Gerhard Bonnet, Anders Ynnerman, Jonas Unger
We present an implementation in CUDA and show real-time performance for an experimental 4 Mpixel multi-sensor HDR video system.