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ORCIDSimone Schaub-Meyer
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- affiliation: TU Darmstadt, Germany
- affiliation (former): ETH Zurich, Switzerland
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2020 – today
- 2024
[c16]Krishnakant Singh, Thanush Navaratnam, Jannik Holmer, Simone Schaub-Meyer, Stefan Roth:
Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images. CVPR Workshops 2024: 2505-2515- [i15]Simon Kiefhaber, Simon Niklaus, Feng Liu, Simone Schaub-Meyer:
Benchmarking Video Frame Interpolation. CoRR abs/2403.17128 (2024) - [i14]Oliver Hahn, Nikita Araslanov, Simone Schaub-Meyer, Stefan Roth:
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals. CoRR abs/2404.16818 (2024) - [i13]Krishnakant Singh, Thanush Navaratnam, Jannik Holmer, Simone Schaub-Meyer, Stefan Roth:
Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images. CoRR abs/2405.20469 (2024) - [i12]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Benchmarking the Attribution Quality of Vision Models. CoRR abs/2407.11910 (2024) - [i11]Krishnakant Singh, Simone Schaub-Meyer, Stefan Roth:
Guided Latent Slot Diffusion for Object-Centric Learning. CoRR abs/2407.17929 (2024) - [i10]Tobias Lingenberg, Markus Reuter, Gopika Sudhakaran, Dominik Gojny, Stefan Roth, Simone Schaub-Meyer:
DIAGen: Diverse Image Augmentation with Generative Models. CoRR abs/2408.14584 (2024) - 2023
- [c15]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Content-Adaptive Downsampling in Convolutional Neural Networks. CVPR Workshops 2023: 4544-4553 - [c14]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods. ICCV 2023: 3958-3968 - [c13]Ali Younes, Simone Schaub-Meyer, Georgia Chalvatzaki:
Entropy-driven Unsupervised Keypoint Representation Learning in Videos. ICML 2023: 40225-40253 - [i9]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Content-Adaptive Downsampling in Convolutional Neural Networks. CoRR abs/2305.09504 (2023) - [i8]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods. CoRR abs/2308.06248 (2023) - 2022
- [j1]Nicholas Ingulfsen
, Simone Schaub-Meyer, Markus Gross, Tobias Günther:
News Globe: Visualization of Geolocalized News Articles. IEEE Computer Graphics and Applications 42(4): 40-51 (2022) - [c12]Krishnakant Singh, Simone Schaub-Meyer, Stefan Roth:
$S^2$-Flow: Joint Semantic and Style Editing of Facial Images. BMVC 2022: 821 - [c11]Moritz Nottebaum, Stefan Roth, Simone Schaub-Meyer:
Efficient Feature Extraction for High-resolution Video Frame Interpolation. BMVC 2022: 825 - [i7]Ali Younes, Simone Schaub-Meyer, Georgia Chalvatzaki:
An information-theoretic approach to unsupervised keypoint representation learning. CoRR abs/2209.15404 (2022) - [i6]Krishnakant Singh, Simone Schaub-Meyer, Stefan Roth:
S2-Flow: Joint Semantic and Style Editing of Facial Images. CoRR abs/2211.12209 (2022) - [i5]Moritz Nottebaum, Stefan Roth, Simone Schaub-Meyer:
Efficient Feature Extraction for High-resolution Video Frame Interpolation. CoRR abs/2211.14005 (2022) - 2021
- [c10]Dustin Carrión-Ojeda, Mahbubul Alam, Sergio Escalera, Ahmed K. Farahat, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Chetan Gupta, Isabelle Guyon, Joël Roman Ky, Xian Yeow Lee, Xin Liu, Felix Mohr, Manh Hung Nguyen, Emmanuel Pintelas, Stefan Roth, Simone Schaub-Meyer, Haozhe Sun, Ihsan Ullah, Joaquin Vanschoren, Lasitha Vidyaratne, Jiamin Wu, Xiaotian Yin:
NeurIPS’22 Cross-Domain MetaDL Challenge: Results and lessons learned. NeurIPS (Competition and Demos) 2021: 50-72 - [c9]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Fast Axiomatic Attribution for Neural Networks. NeurIPS 2021: 19513-19524 - [c8]Nikita Araslanov, Simone Schaub-Meyer, Stefan Roth:
Dense Unsupervised Learning for Video Segmentation. NeurIPS 2021: 25308-25319 - [i4]Nikita Araslanov, Simone Schaub-Meyer, Stefan Roth:
Dense Unsupervised Learning for Video Segmentation. CoRR abs/2111.06265 (2021) - [i3]Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Fast Axiomatic Attribution for Neural Networks. CoRR abs/2111.07668 (2021) - 2020
- [c7]Ali Uzpak, Abdelaziz Djelouah, Simone Schaub-Meyer:
Style Transfer for Keypoint Matching Under Adverse Conditions. 3DV 2020: 1089-1097 - [c6]Ribin Chalumattu, Simone Schaub-Meyer, Robin Wiethüchter, Severin Klingler, Markus Gross:
Simplifying the Process of Creating Augmented Outdoor Scenes. ICME Workshops 2020: 1-6
2010 – 2019
- 2019
- [c5]Abdelaziz Djelouah, Joaquim Campos, Simone Schaub-Meyer, Christopher Schroers:
Neural Inter-Frame Compression for Video Coding. ICCV 2019: 6420-6428 - 2018
- [b1]Simone Schaub-Meyer:
Video Frame Interpolation and Editing with Implicit Motion Estimation. ETH Zurich, Zürich, Switzerland, 2018 - [c4]Simone Meyer, Victor Cornillère, Abdelaziz Djelouah, Christopher Schroers, Markus H. Gross:
Deep Video Color Propagation. BMVC 2018: 128 - [c3]Simone Meyer, Abdelaziz Djelouah, Brian McWilliams, Alexander Sorkine-Hornung, Markus H. Gross, Christopher Schroers:
PhaseNet for Video Frame Interpolation. CVPR 2018: 498-507 - [i2]Simone Meyer, Abdelaziz Djelouah, Brian McWilliams, Alexander Sorkine-Hornung, Markus H. Gross, Christopher Schroers:
PhaseNet for Video Frame Interpolation. CoRR abs/1804.00884 (2018) - [i1]Simone Meyer, Victor Cornillère, Abdelaziz Djelouah, Christopher Schroers, Markus H. Gross:
Deep Video Color Propagation. CoRR abs/1808.03232 (2018) - 2016
- [c2]Simone Meyer, Alexander Sorkine-Hornung, Markus H. Gross:
Phase-Based Modification Transfer for Video. ECCV (3) 2016: 633-648 - 2015
- [c1]Simone Meyer, Oliver Wang, Henning Zimmer, Max Grosse, Alexander Sorkine-Hornung:
Phase-based frame interpolation for video. CVPR 2015: 1410-1418
Coauthor Index
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last updated on 2024-11-04 21:42 CET by the dblp team
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