Tobias Fischer

Orcid: 0000-0001-8227-001X

Affiliations:
  • ETH Zurich, Department of Information Technology and Electrical Engineering, Zurich, Switzerland
  • RWTH Aachen University, Computer Vision Group, Aachen, Germany (2013 - 2020)


According to our database1, Tobias Fischer authored at least 11 papers between 2020 and 2024.

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

Timeline

2020
2021
2022
2023
2024
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5
6
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5
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Legend:

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Links

Online presence:

On csauthors.net:

Bibliography

2024
Dynamic 3D Gaussian Fields for Urban Areas.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation.
Proceedings of the Computer Vision - ECCV 2024, 2024

Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Multi-Level Neural Scene Graphs for Dynamic Urban Environments.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Monocular Quasi-Dense 3D Object Tracking.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

R3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

OVTrack: Open-Vocabulary Multiple Object Tracking.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion.
Proceedings of the Conference on Robot Learning, 2022

2020
Track to Reconstruct and Reconstruct to Track.
IEEE Robotics Autom. Lett., 2020


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