Our paper entitled “Illumination Normalization by Partially Impossible Encoder-Decoder Cost Function” has been accepted for publication at IEEE Winter Conference on Applications of Computer Vision (WACV 2021). We present an image normalization method based on a new strategy for the cost function formulation of encoder-decoder networks to average out all the unimportant information in the input images, in particular, to remove illumination changes and environmental features. Together with our proposed method, we release a synthetic dataset – an extension of SVIRO – of sceneries from three different passenger compartments where each scenery is rendered under ten different illumination and environmental.