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Adapting Pedestrian Detection from Synthetic to Far Infrared Images
Yainuvis Socarras, Sebastian Ramos, David Vazquez, Antonio Lopez and Theo Gevers. 2013. Adapting Pedestrian Detection from Synthetic to Far Infrared Images. ICCV Workshop on Visual Domain Adaptation and Dataset Bias. Sydney, Australy.
We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes.
Adapting Pedestrian Detection from Synthetic to Far Infrared ImagesYainuvis SocarrasSebastian RamosDavid VazquezAntonio LopezTheo Geversopenurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Frefbase.cvc.uab.es%2F&genre=proceeding&title=Adapting%20Pedestrian%20Detection%20from%20Synthetic%20to%20Far%20Infrared%20Images&date=2013&aulast=Yainuvis%20Socarras&au=Sebastian%20Ramos&au=David%20Vazquez&au=Antonio%20Lopez&au=Theo%20Gevers&place=Sydney%2C%20Australy&sid=refbase%3ACVCYainuvis Socarras, Sebastian Ramos, David Vazquez, Antonio Lopez and Theo Gevers. 2013. Adapting Pedestrian Detection from Synthetic to Far Infrared Images. ICCV Workshop on Visual Domain Adaptation and Dataset Bias. Sydney, Australy.2013ConferencePapertextDomain AdaptationFar InfraredPedestrian Detectionfile:http://refbase.cvc.uab.es/files/srv2013.pdfEnglishICCV Workshop on Visual Domain Adaptation and Dataset Bias2013