no code implementations • 30 May 2024 • Andrea Ramazzina, Stefanie Walz, Pragyan Dahal, Mario Bijelic, Felix Heide
We validate the method across day and night scenarios and find that Gated Fields compares favorably to RGB and LiDAR reconstruction methods.
no code implementations • 30 May 2024 • Alessandro Sanvito, Andrea Ramazzina, Stefanie Walz, Mario Bijelic, Felix Heide
To address this issue, we propose HINT, a NeRF-based algorithm able to learn a detailed and complete human model from limited viewing angles.
1 code implementation • 29 May 2024 • Marco Introvigne, Andrea Ramazzina, Stefanie Walz, Dominik Scheuble, Mario Bijelic
Using the novel proposed dataset and hierarchy, we train RECNet, a deep learning model for the classification of environment conditions from a single RGB frame.
no code implementations • 7 May 2024 • David Borts, Erich Liang, Tim Brödermann, Andrea Ramazzina, Stefanie Walz, Edoardo Palladin, Jipeng Sun, David Bruggemann, Christos Sakaridis, Luc van Gool, Mario Bijelic, Felix Heide
Neural fields have been broadly investigated as scene representations for the reproduction and novel generation of diverse outdoor scenes, including those autonomous vehicles and robots must handle.
no code implementations • CVPR 2023 • Stefanie Walz, Mario Bijelic, Andrea Ramazzina, Amanpreet Walia, Fahim Mannan, Felix Heide
We propose Gated Stereo, a high-resolution and long-range depth estimation technique that operates on active gated stereo images.
no code implementations • ICCV 2023 • Andrea Ramazzina, Mario Bijelic, Stefanie Walz, Alessandro Sanvito, Dominik Scheuble, Felix Heide
With data as bottleneck and most of today's training data relying on good weather conditions with inclement weather as outlier, we rely on an inverse rendering approach to reconstruct the scene content.