Kira Maag - RankMe

37 papers A 4B 3Journal 20Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Dance Style Classification Using Laban-Inspired and Frequency-Domain Motion Features. VISAPP (2) Ben Hamscher, Arnold Brosch, Nicolas Binninger, Maksymilian Jan Dejna, Kira Maag
2026	—	`conf`	Spatio-Temporal Attention for Consistent Video Semantic Segmentation in Automated Driving. VISAPP (2) Serin Varghese, Kevin Ross, Fabian Hüger, Kira Maag
2026	J	`jnl`	Spatio-Temporal Attention for Consistent Video Semantic Segmentation in Automated Driving. CoRR Serin Varghese, Kevin Ross, Fabian Hüger, Kira Maag
2026	—	`conf`	VideoGAN-Based Trajectory Proposal for Automated Vehicles. ICAART (2) Annajoyce Mariani, Kira Maag, Hanno Gottschalk
2025	J	`jnl`	Dance Style Classification using Laban-Inspired and Frequency-Domain Motion Features. CoRR Ben Hamscher, Arnold Brosch, Nicolas Binninger, Maksymilian Jan Dejna, Kira Maag
2025	—	`conf`	Multi-Scale Foreground-Background Confidence for Out-of-Distribution Segmentation. VISIGRAPP (2): VISAPP Samuel Marschall, Kira Maag
2025	J	`jnl`	Out-of-Distribution Segmentation via Wasserstein-Based Evidential Uncertainty. CoRR Arnold Brosch, Abdelrahman Eldesokey, Michael Felsberg, Kira Maag
2025	J	`jnl`	Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection. CoRR Tobias Riedlinger, Kira Maag, Hanno Gottschalk
2025	A	`conf`	Transferring Styles for Reduced Texture Bias and Improved Robustness in Semantic Segmentation Networks. ECAI Ben Hamscher, Edgar Heinert, Annika Mütze, Kira Maag, Matthias Rottmann
2025	J	`jnl`	Transferring Styles for Reduced Texture Bias and Improved Robustness in Semantic Segmentation Networks. CoRR Ben Hamscher, Edgar Heinert, Annika Mütze, Kira Maag, Matthias Rottmann
2025	J	`jnl`	VideoGAN-based Trajectory Proposal for Automated Vehicles. CoRR Annajoyce Mariani, Kira Maag, Hanno Gottschalk
2024	J	`jnl`	Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis. CoRR Kira Maag, Roman Resner, Asja Fischer
2024	J	`jnl`	Integrating uncertainty quantification into randomized smoothing based robustness guarantees. CoRR Sina Däubener, Kira Maag, David Krueger, Asja Fischer
2024	J	`jnl`	Multi-Scale Foreground-Background Confidence for Out-of-Distribution Segmentation. CoRR Samuel Marschall, Kira Maag
2024	—	`conf`	Pixel-Wise Gradient Uncertainty for Convolutional Neural Networks Applied to Out-of-Distribution Segmentation. VISIGRAPP (2): VISAPP Kira Maag, Tobias Riedlinger
2024	A	`conf`	Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion. ECAI Edgar Heinert, Matthias Rottmann, Kira Maag, Karsten Kahl
2024	J	`jnl`	Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion. CoRR Edgar Heinert, Matthias Rottmann, Kira Maag, Karsten Kahl
2024	—	`conf`	Uncertainty-Based Detection of Adversarial Attacks in Semantic Segmentation. VISIGRAPP (2): VISAPP Kira Maag, Asja Fischer
2024	A	`conf`	Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. WACV Kira Maag, Asja Fischer
2023	J	`jnl`	Detection of Iterative Adversarial Attacks via Counter Attack. J. Optim. Theory Appl. Matthias Rottmann, Kira Maag, Mathis Peyron, Hanno Gottschalk, Natasa Krejic
2023	—	`conf`	False Negative Reduction in Semantic Segmentation Under Domain Shift Using Depth Estimation. VISIGRAPP (5: VISAPP) Kira Maag, Matthias Rottmann
2023	J	`jnl`	Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation. CoRR Kira Maag, Tobias Riedlinger
2023	J	`jnl`	Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation. CoRR Kira Maag, Asja Fischer
2023	J	`jnl`	Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. CoRR Kira Maag, Asja Fischer
2022	J	`jnl`	False Negative Reduction in Semantic Segmentation under Domain Shift using Depth Estimation. CoRR Kira Maag, Matthias Rottmann
2022	—	`conf`	Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. ACCV (5) Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk
2022	J	`jnl`	Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. CoRR Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk
2021	—	`conf`	An Unsupervised Temporal Consistency (TC) Loss To Improve the Performance of Semantic Segmentation Networks. CVPR Workshops Serin Varghese, Sharat Gujamagadi, Marvin Klingner, Nikhil Kapoor, Andreas Bär, Jan David Schneider, Kira Maag, Peter Schlicht, Fabian Hüger, Tim Fingscheidt
2021	B	`conf`	False Negative Reduction in Video Instance Segmentation using Uncertainty Estimates. ICTAI Kira Maag
2021	J	`jnl`	False Negative Reduction in Video Instance Segmentation using Uncertainty Estimates. CoRR Kira Maag
2021	B	`conf`	Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. IJCNN Kira Maag, Matthias Rottmann, Serin Varghese, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
2021	—	`—`	Prediction Rating and Performance Improvement for Segmentation Networks by Time-Dynamic Uncertainty Estimates. Kira Maag
2020	A	`conf`	Detection of False Positive and False Negative Samples in Semantic Segmentation. DATE Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
2020	J	`jnl`	Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. CoRR Kira Maag, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
2020	B	`conf`	Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks. ICTAI Kira Maag, Matthias Rottmann, Hanno Gottschalk
2019	J	`jnl`	Detection of False Positive and False Negative Samples in Semantic Segmentation. CoRR Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
2019	J	`jnl`	Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks. CoRR Kira Maag, Matthias Rottmann, Hanno Gottschalk