3 accepted papers
In monocular depth estimation, uncertainty estimation approaches mainly target the data uncertainty introduced by image noise. In contrast to prior work, we address the uncertainty due to lack of knowledge, which is relevant for the detection of data not represented by the training distribution, the…
In this work, we present MotionMixer, an efficient 3D human body pose forecasting model based solely on multi-layer perceptrons (MLPs). MotionMixer learns the spatial-temporal 3D body pose dependencies by sequentially mixing both modalities. Given a stacked sequence of 3D body poses, a spatial-MLP e…
Testing and verification is still an open issue on the way to fully automated driving. Simulations can help to reduce the required testing efforts, however, classical simulators based on physical models and heuristics, such as the intelligent driver model (IDM), show limited model accuracy on a micr…