Tobias Christian Nauen

According to our database, Tobias Christian Nauen authored at least 9 papers between 2023 and 2025.

Collaborative distances:

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

2025

ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation.

Tobias Christian Nauen, Brian B. Moser, Federico Raue, Stanislav Frolov, Andreas Dengel

CoRR, March, 2025

A Study in Dataset Distillation for Image Super-Resolution.

Tobias Dietz, Brian B. Moser, Tobias Christian Nauen, Federico Raue, Stanislav Frolov, Andreas Dengel

CoRR, February, 2025

Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers.

Tobias Christian Nauen, Sebastian Palacio, Federico Raue, Andreas Dengel

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

2024

Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning.

Brian B. Moser, Federico Raue, Tobias Christian Nauen, Stanislav Frolov, Andreas Dengel

CoRR, 2024

Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning.

Arundhati S. Shanbhag, Brian B. Moser, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Andreas Dengel

CoRR, 2024

Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution.

Brian B. Moser, Stanislav Frolov, Tobias Christian Nauen, Federico Raue, Andreas Dengel

CoRR, 2024

A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift.

Sanath Budakegowdanadoddi Nagaraju, Brian B. Moser, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Andreas Dengel

CoRR, 2024

TaylorShift: Shifting the Complexity of Self-attention from Squared to Linear (and Back) Using Taylor-Softmax.

Tobias Christian Nauen, Sebastian Palacio, Andreas Dengel

Proceedings of the Pattern Recognition - 27th International Conference, 2024

2023

Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers.

Tobias Christian Nauen, Sebastian Palacio, Andreas Dengel

CoRR, 2023