5 papers
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi +3
We present a learning-based method for synthesizing novel views of complex scenes using only unstructured collections of in-the-wild photographs. We build on Neural Radiance Fields…
VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry
Noha Radwan, Abhinav Valada, Wolfram Burgard
Semantic understanding and localization are fundamental enablers of robot autonomy that have for the most part been tackled as disjoint problems. While deep learning has enabled re…
Deep Auxiliary Learning for Visual Localization and Odometry
Abhinav Valada, Noha Radwan, Wolfram Burgard
Localization is an indispensable component of a robot's autonomy stack that enables it to determine where it is in the environment, essentially making it a precursor for any action…
Why did the Robot Cross the Road? - Learning from Multi-Modal Sensor Data for Autonomous Road Crossing
Noha Radwan, Wera Winterhalter, Christian Dornhege +1
We consider the problem of developing robots that navigate like pedestrians on sidewalks through city centers for performing various tasks including delivery and surveillance. One…
Topometric Localization with Deep Learning
Gabriel L. Oliveira, Noha Radwan, Wolfram Burgard +1
Compared to LiDAR-based localization methods, which provide high accuracy but rely on expensive sensors, visual localization approaches only require a camera and thus are more cost…