Noha Radwan

According to our database, Noha Radwan authored at least 13 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes.

Suhani Vora, Noha Radwan, Klaus Greff, Henning Meyer, Kyle Genova, Mehdi S. M. Sajjadi, Etienne Pot, Andrea Tagliasacchi, Daniel Duckworth

Trans. Mach. Learn. Res., 2022

Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations.

Mehdi S. M. Sajjadi, Henning Meyer, Etienne Pot, Urs Bergmann, Klaus Greff, Noha Radwan, Suhani Vora, Mario Lucic, Daniel Duckworth, Alexey Dosovitskiy, Jakob Uszkoreit, Thomas A. Funkhouser, Andrea Tagliasacchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs.

Michael Niemeyer, Jonathan T. Barron, Ben Mildenhall, Mehdi S. M. Sajjadi, Andreas Geiger, Noha Radwan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Kubric: A scalable dataset generator.

Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections.

Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan T. Barron, Alexey Dosovitskiy, Daniel Duckworth

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Multimodal interaction-aware motion prediction for autonomous street crossing.

Noha Radwan, Wolfram Burgard, Abhinav Valada

Int. J. Robotics Res., 2020

2019

Leveraging sparse and dense features for reliable state estimation in urban environments.

Noha Radwan

PhD thesis, 2019

2018

VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry.

Noha Radwan, Abhinav Valada, Wolfram Burgard

IEEE Robotics Autom. Lett., 2018

Deep Auxiliary Learning for Visual Localization and Odometry.

Abhinav Valada, Noha Radwan, Wolfram Burgard

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

Topometric Localization with Deep Learning.

Gabriel L. Oliveira, Noha Radwan, Wolfram Burgard, Thomas Brox

Proceedings of the Robotics Research, The 18th International Symposium, 2017

Perspectives on Deep Multimodel Robot Learning.

Wolfram Burgard, Abhinav Valada, Noha Radwan, Tayyab Naseer, Jingwei Zhang, Johan Vertens, Oier Mees, Andreas Eitel, Gabriel L. Oliveira

Proceedings of the Robotics Research, The 18th International Symposium, 2017

Why did the robot cross the road? - Learning from multi-modal sensor data for autonomous road crossing.

Noha Radwan, Wera Winterhalter, Christian Dornhege, Wolfram Burgard

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

2016

Do you see the bakery? Leveraging geo-referenced texts for global localization in public maps.

Noha Radwan, Gian Diego Tipaldi, Luciano Spinello, Wolfram Burgard

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016