Tobias Riedlinger

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 13

Top Topics

Rapid Prototyping

Active Learning

Convolutional Neural Networks

Top Venues

VISIGRAPP (2): VISAPP

Publications

Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. VISIGRAPP (2): VISAPP (2024)
Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann
Identifying Label Errors in Object Detection Datasets by Loss Inspection. WACV (2024)
Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann
Deep Active Learning with Noisy Oracle in Object Detection. VISIGRAPP (2): VISAPP (2024)
Kira Maag, Tobias Riedlinger
Pixel-Wise Gradient Uncertainty for Convolutional Neural Networks Applied to Out-of-Distribution Segmentation. VISIGRAPP (2): VISAPP (2024)
Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann
Identifying Label Errors in Object Detection Datasets by Loss Inspection. CoRR (2023)
Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann
LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. DAGM (2023)
Kira Maag, Tobias Riedlinger
Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation. CoRR (2023)
Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann
Deep Active Learning with Noisy Oracle in Object Detection. CoRR (2023)
Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. WACV (2023)
Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann
LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. CoRR (2023)
Julian Burghoff, Robin Chan, Hanno Gottschalk, Annika Mütze, Tobias Riedlinger, Matthias Rottmann, Marius Schubert
Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning. CoRR (2022)
Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. CoRR (2022)
Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. CoRR (2021)