Tobias Gruber

Orcid: 0000-0002-6008-1397

According to our database1, Tobias Gruber authored at least 14 papers between 2017 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2020
Real-time super-resolved depth estimation for self-driving cars from multiple gated images.
PhD thesis, 2020

Uncertainty depth estimation with gated images for 3D reconstruction.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Benchmarking Automotive LiDAR Performance in Arctic Conditions.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Seeing Through Fog Without Seeing Fog: Deep Sensor Fusion in the Absence of Labeled Training Data.
CoRR, 2019

Gated2Depth: Real-time Dense Lidar from Gated Images.
CoRR, 2019

Gated2Depth: Real-Time Dense Lidar From Gated Images.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Recovering the Unseen: Benchmarking the Generalization of Enhancement Methods to Real World Data in Heavy Fog.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios.
Proceedings of the 2019 International Conference on 3D Vision, 2019

2018
Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

Learning Super-resolved Depth from Active Gated Imaging.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2017
Scaling Deep Learning-Based Decoding of Polar Codes via Partitioning.
Proceedings of the 2017 IEEE Global Communications Conference, 2017

On deep learning-based channel decoding.
Proceedings of the 51st Annual Conference on Information Sciences and Systems, 2017


  Loading...