  We investigate the effect of style and category similarity in multiple
datasets used for object detection pretraining. We find that including an
additional stage of object-detection pretraining can increase the detection
performance considerably. While our experiments suggest that style similarities
between pre-training and target datasets are less important than matching
categories, further experiments are needed to verify this hypothesis.
