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Update experiments.tex

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@ -5,7 +5,7 @@ computations. To make our code easy to extend and flexible, we build on
the TensorFlow Object detection API \cite{TensorFlowObjectDetection}, which provides a Faster R-CNN baseline
implementation.
On top of this, we implemented Mask R-CNN and the Feature Pyramid Network (FPN)
as well all extensions for motion estimation and related evaluations
as well as extensions for motion estimation and related evaluations
and postprocessings. In addition, we generated all ground truth for
Motion R-CNN in the form of TFRecords from the raw Virtual KITTI
data to enable fast loading during training.