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dc.contributor.authorMüller, Matthias
dc.contributor.authorCasser, Vincent
dc.contributor.authorLahoud, Jean
dc.contributor.authorSmith, Neil
dc.contributor.authorGhanem, Bernard
dc.date.accessioned2018-04-08T07:45:41Z
dc.date.available2018-04-08T07:45:41Z
dc.date.issued2018-03-24
dc.identifier.citationMüller M, Casser V, Lahoud J, Smith N, Ghanem B (2018) Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications. International Journal of Computer Vision. Available: http://dx.doi.org/10.1007/s11263-018-1073-7.
dc.identifier.issn0920-5691
dc.identifier.issn1573-1405
dc.identifier.doi10.1007/s11263-018-1073-7
dc.identifier.urihttp://hdl.handle.net/10754/627416
dc.description.abstractWe present a photo-realistic training and evaluation simulator (Sim4CV) (http://www.sim4cv.org) with extensive applications across various fields of computer vision. Built on top of the Unreal Engine, the simulator integrates full featured physics based cars, unmanned aerial vehicles (UAVs), and animated human actors in diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous driving using supervised learning. The simulator fully integrates both several state-of-the-art tracking algorithms with a benchmark evaluation tool and a deep neural network architecture for training vehicles to drive autonomously. It generates synthetic photo-realistic datasets with automatic ground truth annotations to easily extend existing real-world datasets and provides extensive synthetic data variety through its ability to reconfigure synthetic worlds on the fly using an automatic world generation tool.
dc.description.sponsorshipThis work was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research through the VCC funding.
dc.publisherSpringer Nature
dc.relation.urlhttp://link.springer.com/article/10.1007/s11263-018-1073-7
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/s11263-018-1073-7
dc.subjectSimulator
dc.subjectUnreal Engine 4
dc.subjectObject tracking
dc.subjectAutonomous driving
dc.subjectDeep learning
dc.subjectImitation learning
dc.titleSim4CV: A Photo-Realistic Simulator for Computer Vision Applications
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journalInternational Journal of Computer Vision
dc.eprint.versionPost-print
kaust.personMüller, Matthias
kaust.personCasser, Vincent
kaust.personLahoud, Jean
kaust.personSmith, Neil
kaust.personGhanem, Bernard
refterms.dateFOA2019-03-24T00:00:00Z
dc.date.published-online2018-03-24
dc.date.published-print2018-09


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