218 citations · 219 across the 8 of their papers we have counts for
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cs.CV2017
Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps
Florian Piewak, Timo Rehfeld, Michael Weber +1
Grid maps are widely used in robotics to represent obstacles in the environment and differentiating dynamic objects from static infrastructure is essential for many practical appli…
cs.CV2017
Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps (Masters Thesis)
Florian Piewak
One of the most important parts of environment perception is the detection of obstacles in the surrounding of the vehicle. To achieve that, several sensors like radars, LiDARs and…
cs.CV2017
RegNet: Multimodal Sensor Registration Using Deep Neural Networks
Nick Schneider, Florian Piewak, Christoph Stiller +1
In this paper, we present RegNet, the first deep convolutional neural network (CNN) to infer a 6 degrees of freedom (DOF) extrinsic calibration between multimodal sensors, exemplif…