Marvin Klingner

Orcid: 0000-0001-7675-750X

According to our database1, Marvin Klingner authored at least 25 papers between 2020 and 2024.

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

Timeline

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PhD thesis 
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Bibliography

2024
S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving.
CoRR, 2024

2023
X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation.
Mach. Vis. Appl., July, 2023

Multi-Task and Multi-Domain Learning for Semantic Segmentation and Depth Estimation: Offline and Online Methods.
PhD thesis, 2023

A Super-Resolution Training Paradigm Based on Low-Resolution Data Only to Surpass the Technical Limits of STEM and STM Microscopy.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

X<sup>3</sup>KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

End-to-end Amodal Video Instance Segmentation.
Proceedings of the 34th British Machine Vision Conference Workshop Proceedings, 2023

2022
SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras.
IEEE Trans. Intell. Transp. Syst., 2022

Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation.
IEEE Trans. Intell. Transp. Syst., 2022

Unsupervised BatchNorm Adaptation (UBNA): A Domain Adaptation Method for Semantic Segmentation Without Using Source Domain Representations.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2022

3DHD CityScenes: High-Definition Maps in High-Density Point Clouds.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Detecting Adversarial Perturbations in Multi-Task Perception.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Online Performance Prediction of Perception DNNs by Multi-Task Learning With Depth Estimation.
IEEE Trans. Intell. Transp. Syst., 2021

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety.
CoRR, 2021

SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Continual Unsupervised Domain Adaptation for Semantic Segmentation by Online Frequency Domain Style Transfer.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

DNN-Based Recognition of Pole-Like Objects in LiDAR Point Clouds.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

An Unsupervised Temporal Consistency (TC) Loss To Improve the Performance of Semantic Segmentation Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Improving Online Performance Prediction for Semantic Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old Labels.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Self-supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance.
Proceedings of the Computer Vision - ECCV 2020, 2020

Self-Supervised Domain Mismatch Estimation for Autonomous Perception.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Robust Semantic Segmentation by Redundant Networks With a Layer-Specific Loss Contribution and Majority Vote.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020


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