1 citations · 1 across the 2 of their papers we have counts for
4 papers · 1 filter
Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation
Niklas Hanselmann, Nick Schneider, Benedikt Ortelt +1
In order to handle the challenges of autonomous driving, deep learning has proven to be crucial in tackling increasingly complex tasks, such as 3D detection or instance segmentatio…
Boosting LiDAR-based Semantic Labeling by Cross-Modal Training Data Generation
Florian Piewak, Peter Pinggera, Manuel Schäfer +6
Mobile robots and autonomous vehicles rely on multi-modal sensor setups to perceive and understand their surroundings. Aside from cameras, LiDAR sensors represent a central compone…
Sparsity Invariant CNNs
Jonas Uhrig, Nick Schneider, Lukas Schneider +3
In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditi…
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…