no code implementations • 1 Apr 2022 • Ramy Battrawy, René Schuster, Mohammad-Ali Nikouei Mahani, Didier Stricker
The proposed RMS-FlowNet is a novel end-to-end learning-based architecture for accurate and efficient scene flow estimation which can operate on point clouds of high density.
no code implementations • CVPR 2022 • Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Mohammad-Ali Nikouei Mahani, Nassir Navab, Benjamin Busam, Federico Tombari
Despite training only on a standard dataset, such as KITTI, augmenting with our vector fields significantly improves the generalization to differently shaped objects and scenes.
no code implementations • 4 Oct 2021 • Stefano Gasperini, Jan Haug, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Benjamin Busam, Federico Tombari
Estimating the uncertainty of a neural network plays a fundamental role in safety-critical settings.
no code implementations • 28 Oct 2020 • Stefano Gasperini, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Federico Tombari
Panoptic segmentation has recently unified semantic and instance segmentation, previously addressed separately, thus taking a step further towards creating more comprehensive and efficient perception systems.