no code implementations • CVPR 2022 • Oliver Zendel, Matthias Schörghuber, Bernhard Rainer, Markus Murschitz, Csaba Beleznai
The dataset consists of more than 5000 unique driving scenes from all over the world with a focus on visually challenging scenes, such as diverse weather conditions, lighting situations, and camera characteristics.
no code implementations • CVPR 2019 • Oliver Zendel, Markus Murschitz, Marcel Zeilinger, Daniel Steininger, Sara Abbasi, Csaba Beleznai
In this paper, we intro-duce the first public dataset for semantic scene understand-ing for trains and trams: RailSem19.
no code implementations • ECCV 2018 • Oliver Zendel, Katrin Honauer, Markus Murschitz, Daniel Steininger, Gustavo Fernandez Dominguez
We have conducted a thorough risk analysis to identify situations and aspects that can reduce the output performance for these tasks.
no code implementations • CVPR 2017 • Oliver Zendel, Katrin Honauer, Markus Murschitz, Martin Humenberger, Gustavo Fernandez Dominguez
However, major questions concerning quality and usefulness of test data for CV evaluation are still unanswered.
no code implementations • ICCV 2015 • Oliver Zendel, Markus Murschitz, Martin Humenberger, Wolfgang Herzner
This checklist can be used to evaluate existing test datasets by quantifying the amount of covered hazards.