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ORCIDDaniel Cremers
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- affiliation: Technical University Munich, Germany
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2020 – today
- 2023
[j90]Qadeer Khan
, Idil Sülö, Melis Öcal, Daniel Cremers:
Learning vision based autonomous lateral vehicle control without supervision. Appl. Intell. 53(16): 19186-19198 (2023)- [j89]Zhenzhang Ye, Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers:
A Cutting-Plane Method for Sublabel-Accurate Relaxation of Problems with Product Label Spaces. Int. J. Comput. Vis. 131(1): 346-362 (2023) - [j88]Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers:
E-NeRF: Neural Radiance Fields From a Moving Event Camera. IEEE Robotics Autom. Lett. 8(3): 1587-1594 (2023) - [c336]Simon Weber, Nikolaus Demmel, Tin Chon Chan, Daniel Cremers:
Power Bundle Adjustment for Large-Scale 3D Reconstruction. CVPR 2023: 281-289 - [c335]Linus Härenstam-Nielsen, Niclas Zeller, Daniel Cremers:
Semidefinite Relaxations for Robust Multiview Triangulation. CVPR 2023: 749-757 - [c334]Olaf Wysocki, Yan Xia, Magdalena Wysocki, Eleonora Grilli, Ludwig Hoegner, Daniel Cremers, Uwe Stilla:
Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks. CVPR Workshops 2023: 6548-6558 - [c333]Felix Wimbauer, Nan Yang, Christian Rupprecht, Daniel Cremers:
Behind the Scenes: Density Fields for Single View Reconstruction. CVPR 2023: 9076-9086 - [c332]Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers:
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares. CVPR 2023: 13102-13112 - [c331]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
G-MSM: Unsupervised Multi-Shape Matching with Graph-Based Affinity Priors. CVPR 2023: 22762-22772 - [c330]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. ICML 2023: 30252-30284 - [c329]Christian Tomani, Futa Kai Waseda, Yuesong Shen, Daniel Cremers:
Beyond In-Domain Scenarios: Robust Density-Aware Calibration. ICML 2023: 34344-34368 - [c328]George Eskandar, Youssef Farag, Tarun Yenamandra, Daniel Cremers, Karim Guirguis, Bin Yang:
Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes. IV 2023: 1-8 - [c327]Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers:
Neural Implicit Representations for Physical Parameter Inference from a Single Video. WACV 2023: 2092-2102 - [c326]Lu Sang, Bjoern Haefner, Xingxing Zuo, Daniel Cremers:
High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF. WACV 2023: 3105-3114 - [i195]Patrick Wenzel, Nan Yang, Rui Wang, Niclas Zeller, Daniel Cremers:
4Seasons: Benchmarking Visual SLAM and Long-Term Localization for Autonomous Driving in Challenging Conditions. CoRR abs/2301.01147 (2023) - [i194]Dekai Zhu, Qadeer Khan, Daniel Cremers:
Multi-Vehicle Trajectory Prediction at Intersections using State and Intention Information. CoRR abs/2301.02561 (2023) - [i193]Felix Wimbauer, Nan Yang, Christian Rupprecht, Daniel Cremers:
Behind the Scenes: Density Fields for Single View Reconstruction. CoRR abs/2301.07668 (2023) - [i192]Linus Härenstam-Nielsen, Niclas Zeller, Daniel Cremers:
Semidefinite Relaxations for Robust Multiview Triangulation. CoRR abs/2301.11431 (2023) - [i191]Christian Tomani, Futa Waseda, Yuesong Shen, Daniel Cremers:
Beyond In-Domain Scenarios: Robust Density-Aware Calibration. CoRR abs/2302.05118 (2023) - [i190]Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang, Moritz Zaiss, Andreas Maier, Daniel Cremers:
Scale-Equivariant Deep Learning for 3D Data. CoRR abs/2304.05864 (2023) - [i189]Olaf Wysocki, Yan Xia, Magdalena Wysocki, Eleonora Grilli, Ludwig Hoegner, Daniel Cremers, Uwe Stilla:
Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks. CoRR abs/2305.06314 (2023) - [i188]Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer, Daniel Cremers, Andreas K. Maier, Moritz Zaiss:
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution. CoRR abs/2305.07524 (2023) - [i187]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Non-Separable Multi-Dimensional Network Flows for Visual Computing. CoRR abs/2305.08628 (2023) - [i186]Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers:
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares. CoRR abs/2305.09527 (2023) - [i185]George Eskandar, Youssef Farag, Tarun Yenamandra, Daniel Cremers, Karim Guirguis, Bin Yang:
Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes. CoRR abs/2305.09602 (2023) - [i184]Lu Sang, Abhishek Saroha, Maolin Gao, Daniel Cremers:
Weight-Aware Implicit Geometry Reconstruction with Curvature-Guided Sampling. CoRR abs/2306.02099 (2023) - [i183]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. CoRR abs/2307.07753 (2023) - [i182]Marc Botet Colomer, Pier Luigi Dovesi, Theodoros Panagiotakopoulos, Joao Frederico Carvalho, Linus Härenstam-Nielsen, Hossein Azizpour, Hedvig Kjellström, Daniel Cremers, Matteo Poggi:
To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation. CoRR abs/2307.15063 (2023) - [i181]Yining Ma, Qadeer Khan, Daniel Cremers:
Multi Agent Navigation in Unconstrained Environments using a Centralized Attention based Graphical Neural Network Controller. CoRR abs/2307.16727 (2023) - [i180]Jonathan Schmidt, Qadeer Khan, Daniel Cremers:
LiDAR View Synthesis for Robust Vehicle Navigation Without Expert Labels. CoRR abs/2308.01424 (2023) - [i179]Jiaxin Pan, Changyao Zhou, Mariia Gladkova, Qadeer Khan, Daniel Cremers:
Robust Autonomous Vehicle Pursuit without Expert Steering Labels. CoRR abs/2308.08380 (2023) - [i178]Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard:
SIGMA: Scale-Invariant Global Sparse Shape Matching. CoRR abs/2308.08393 (2023) - [i177]Viktoria Ehm, Paul Roetzer, Marvin Eisenberger, Maolin Gao, Florian Bernard, Daniel Cremers:
Geometrically Consistent Partial Shape Matching. CoRR abs/2309.05013 (2023) - [i176]Yiming Shan, Yan Xia, Yuhong Chen, Daniel Cremers:
SCP: Scene Completion Pre-training for 3D Object Detection. CoRR abs/2309.06199 (2023) - 2022
- [j87]Hamid Rezatofighi, Tianyu Zhu, Roman Kaskman, Farbod T. Motlagh, Javen Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Learn to Predict Sets Using Feed-Forward Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9011-9025 (2022) - [j86]Lukas von Stumberg, Daniel Cremers:
DM-VIO: Delayed Marginalization Visual-Inertial Odometry. IEEE Robotics Autom. Lett. 7(2): 1408-1415 (2022) - [j85]Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. SIAM J. Imaging Sci. 15(3): 1253-1281 (2022) - [c325]Zhenzhang Ye, Tarun Yenamandra, Florian Bernard, Daniel Cremers:
Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections. AAAI 2022: 3125-3133 - [c324]Hang Li, Qadeer Khan, Volker Tresp, Daniel Cremers:
Biologically Inspired Neural Path Finding. BI 2022: 329-342 - [c323]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRL 2022: 161-174 - [c322]Paul Roetzer, Paul Swoboda, Daniel Cremers, Florian Bernard:
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching. CVPR 2022: 428-438 - [c321]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers:
A Unified Framework for Implicit Sinkhorn Differentiation. CVPR 2022: 499-508 - [c320]Dominik Muhle, Lukas Koestler, Nikolaus Demmel, Florian Bernard, Daniel Cremers:
The Probabilistic Normal Epipolar Constraint for Frame- To-Frame Rotation Optimization under Uncertain Feature Positions. CVPR 2022: 1809-1818 - [c319]Christiane Sommer, Lu Sang, David Schubert, Daniel Cremers:
Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction. CVPR 2022: 6270-6279 - [c318]Aysim Toker, Lukas Kondmann, Mark Weber, Marvin Eisenberger, Andrés Camero, Jingliang Hu, Ariadna Pregel Hoderlein, Çaglar Senaras, Timothy Davis, Daniel Cremers, Giovanni Marchisio, Xiao Xiang Zhu, Laura Leal-Taixé:
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. CVPR 2022: 21126-21135 - [c317]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. ECCV (13) 2022: 555-569 - [c316]Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner:
Intrinsic Neural Fields: Learning Functions on Manifolds. ECCV (2) 2022: 622-639 - [c315]Dominik Rößle, Daniel Cremers, Torsten Schön:
Perceiver Hopfield Pooling for Dynamic Multi-modal and Multi-instance Fusion. ICANN (1) 2022: 599-610 - [c314]Deepan Das, Qadeer Khan, Daniel Cremers:
Ventriloquist-Net: Leveraging Speech Cues for Emotive Talking Head Generation. ICIP 2022: 1716-1720 - [c313]Zhakshylyk Nurlanov, Daniel Cremers, Florian Bernard:
Efficient and Flexible Sublabel-Accurate Energy Minimization. ICPR 2022: 175-181 - [c312]Florian Müller, Qadeer Khan, Daniel Cremers:
Lateral Ego-Vehicle Control Without Supervision Using Point Clouds. ICPRAI (1) 2022: 477-488 - [c311]Qing Cheng, Niclas Zeller, Daniel Cremers:
Vision-Based Large-scale 3D Semantic Mapping for Autonomous Driving Applications. ICRA 2022: 9235-9242 - [c310]Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers:
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. IROS 2022: 3777-3784 - [c309]Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers:
What Makes Graph Neural Networks Miscalibrated? NeurIPS 2022 - [c308]Yuesong Shen, Daniel Cremers:
Deep Combinatorial Aggregation. NeurIPS 2022 - [e12]Björn Andres, Florian Bernard, Daniel Cremers, Simone Frintrop, Bastian Goldlücke, Ivo Ihrke:
Pattern Recognition - 44th DAGM German Conference, DAGM GCPR 2022, Konstanz, Germany, September 27-30, 2022, Proceedings. Lecture Notes in Computer Science 13485, Springer 2022, ISBN 978-3-031-16787-4 [contents] - [i175]Lukas von Stumberg, Daniel Cremers:
DM-VIO: Delayed Marginalization Visual-Inertial Odometry. CoRR abs/2201.04114 (2022) - [i174]Qing Cheng, Niclas Zeller, Daniel Cremers:
Vision-based Large-scale 3D Semantic Mapping for Autonomous Driving Applications. CoRR abs/2203.01087 (2022) - [i173]Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner:
Intrinsic Neural Fields: Learning Functions on Manifolds. CoRR abs/2203.07967 (2022) - [i172]Florian Müller, Qadeer Khan, Daniel Cremers:
Lateral Ego-Vehicle Control without Supervision using Point Clouds. CoRR abs/2203.10662 (2022) - [i171]Aysim Toker, Lukas Kondmann, Mark Weber, Marvin Eisenberger, Andrés Camero, Jingliang Hu, Ariadna Pregel Hoderlein, Çaglar Senaras, Timothy Davis, Daniel Cremers, Giovanni Marchisio, Xiao Xiang Zhu, Laura Leal-Taixé:
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. CoRR abs/2203.12560 (2022) - [i170]Tarun Yenamandra, Ayush Tewari, Nan Yang, Florian Bernard, Christian Theobalt, Daniel Cremers:
HDSDF: Hybrid Directional and Signed Distance Functions for Fast Inverse Rendering. CoRR abs/2203.16284 (2022) - [i169]Dominik Muhle, Lukas Koestler, Nikolaus Demmel, Florian Bernard, Daniel Cremers:
The Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions. CoRR abs/2204.02256 (2022) - [i168]Abhishek Saroha, Marvin Eisenberger, Tarun Yenamandra, Daniel Cremers:
Implicit Shape Completion via Adversarial Shape Priors. CoRR abs/2204.10060 (2022) - [i167]Paul Roetzer, Paul Swoboda, Daniel Cremers, Florian Bernard:
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching. CoRR abs/2204.12805 (2022) - [i166]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Power Bundle Adjustment for Large-Scale 3D Reconstruction. CoRR abs/2204.12834 (2022) - [i165]Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers:
Neural Implicit Representations for Physical Parameter Inference from a Single Video. CoRR abs/2204.14030 (2022) - [i164]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers:
A Unified Framework for Implicit Sinkhorn Differentiation. CoRR abs/2205.06688 (2022) - [i163]Michael Schleiss, Fahmi Rouatbi, Daniel Cremers:
VPAIR - Aerial Visual Place Recognition and Localization in Large-scale Outdoor Environments. CoRR abs/2205.11567 (2022) - [i162]Christian Tomani, Daniel Cremers:
CHALLENGER: Training with Attribution Maps. CoRR abs/2205.15094 (2022) - [i161]Hang Li, Qadeer Khan, Volker Tresp, Daniel Cremers:
Biologically Inspired Neural Path Finding. CoRR abs/2206.05971 (2022) - [i160]Zhakshylyk Nurlanov, Daniel Cremers, Florian Bernard:
Efficient and Flexible Sublabel-Accurate Energy Minimization. CoRR abs/2206.09596 (2022) - [i159]Sherwin Bahmani, Oliver Hahn, Eduard Zamfir, Nikita Araslanov, Daniel Cremers, Stefan Roth:
Semantic Self-adaptation: Enhancing Generalization with a Single Sample. CoRR abs/2208.05788 (2022) - [i158]Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers:
E-NeRF: Neural Radiance Fields from a Moving Event Camera. CoRR abs/2208.11300 (2022) - [i157]Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers:
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. CoRR abs/2209.14965 (2022) - [i156]Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers:
What Makes Graph Neural Networks Miscalibrated? CoRR abs/2210.06391 (2022) - [i155]Yuesong Shen, Daniel Cremers:
Deep Combinatorial Aggregation. CoRR abs/2210.06436 (2022) - [i154]Lu Sang, Bjoern Haefner, Xingxing Zuo, Daniel Cremers:
High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF. CoRR abs/2210.12202 (2022) - [i153]Hans Hao-Hsun Hsu, Yuesong Shen, Daniel Cremers:
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs. CoRR abs/2210.15575 (2022) - [i152]Yan Xia, Mariia Gladkova, Rui Wang, João F. Henriques, Daniel Cremers, Uwe Stilla:
PVT3D: Point Voxel Transformers for Place Recognition from Sparse Lidar Scans. CoRR abs/2211.12542 (2022) - [i151]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors. CoRR abs/2212.02910 (2022) - [i150]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRR abs/2212.02988 (2022) - [i149]Mohammed Brahimi, Bjoern Haefner, Tarun Yenamandra, Bastian Goldluecke, Daniel Cremers:
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering. CoRR abs/2212.04968 (2022) - [i148]Simon Klenk, David Bonello, Lukas Koestler, Daniel Cremers:
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras. CoRR abs/2212.10368 (2022) - 2021
- [j84]Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian Reid, Stefan Roth, Laura Leal-Taixé:
MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking. Int. J. Comput. Vis. 129(4): 845-881 (2021) - [c307]Bjoern Haefner, Simon Green, Alan Oursland, Daniel Andersen, Michael Goesele, Daniel Cremers, Richard A. Newcombe, Thomas Whelan:
Recovering Real-World Reflectance Properties and Shading From HDR Imagery. 3DV 2021: 1075-1084 - [c306]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Shortest Paths in Graphs with Matrix-Valued Edges: Concepts, Algorithm and Application to 3D Multi-Shape Analysis. 3DV 2021: 1186-1195 - [c305]Qadeer Khan, Patrick Wenzel, Daniel Cremers:
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry. AISTATS 2021: 3781-3789 - [c304]Lukas Koestler, Nan Yang, Niclas Zeller, Daniel Cremers:
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo. CoRL 2021: 34-45 - [c303]Felix Wimbauer, Nan Yang, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments From a Single Moving Camera. CVPR 2021: 6112-6122 - [c302]Marvin Eisenberger, David Novotný, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers, Andrea Vedaldi:
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go. CVPR 2021: 7473-7483 - [c301]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. CVPR 2021: 10124-10132 - [c300]Yan Xia, Yusheng Xu, Shuang Li, Rui Wang, Juan Du, Daniel Cremers, Uwe Stilla:
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud Based Place Recognition. CVPR 2021: 11348-11357 - [c299]Nikolaus Demmel, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Bundle Adjustment for Large-Scale Reconstruction. CVPR 2021: 11723-11732 - [c298]Tarun Yenamandra, Ayush Tewari, Florian Bernard, Hans-Peter Seidel, Mohamed Elgharib, Daniel Cremers, Christian Theobalt:
i3DMM: Deep Implicit 3D Morphable Model of Human Heads. CVPR 2021: 12803-12813 - [c297]Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard:
Isometric Multi-Shape Matching. CVPR 2021: 14183-14193 - [c296]Zhenzhang Ye, Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers:
Sublabel-Accurate Multilabeling Meets Product Label Spaces. GCPR 2021: 3-17 - [c295]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Multidirectional Conjugate Gradients for Scalable Bundle Adjustment. GCPR 2021: 712-724 - [c294]Nikolaus Demmel, David Schubert, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Marginalization for Sliding-Window Bundle Adjustment. ICCV 2021: 13240-13248 - [c293]Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer:
Variational Data Assimilation with a Learned Inverse Observation Operator. ICML 2021: 3449-3458 - [c292]Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers:
Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry. ICRA 2021: 9608-9614 - [c291]Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers:
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. ICRA 2021: 14360-14366 - [c290]Simon Klenk, Jason Chui, Nikolaus Demmel, Daniel Cremers:
TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset. IROS 2021: 8601-8608 - [c289]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. IROS 2021: 8737-8744 - [c288]Florian Bernard, Daniel Cremers, Johan Thunberg:
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation. NeurIPS 2021: 25256-25266 - [c287]Mark Weber, Jun Xie, Maxwell D. Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixé, Liang-Chieh Chen:
STEP: Segmenting and Tracking Every Pixel. NeurIPS Datasets and Benchmarks 2021 - [c286]Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs:
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization. SSVM 2021: 204-215 - [c285]Yu Wang, Yuesong Shen, Daniel Cremers:
Explicit pairwise factorized graph neural network for semi-supervised node classification. UAI 2021: 1979-1987 - [i147]Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers:
Tight Integration of Feature-Based Relocalization in Monocular Direct Visual Odometry. CoRR abs/2102.01191 (2021) - [i146]Philip Müller, Vladimir Golkov, Valentina Tomassini, Daniel Cremers:
Rotation-Equivariant Deep Learning for Diffusion MRI. CoRR abs/2102.06942 (2021) - [i145]Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer:
Variational Data Assimilation with a Learned Inverse Observation Operator. CoRR abs/2102.11192 (2021) - [i144]Mark Weber, Jun Xie, Maxwell D. Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixé, Liang-Chieh Chen:
STEP: Segmenting and Tracking Every Pixel. CoRR abs/2102.11859 (2021) - [i143]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. CoRR abs/2102.12182 (2021) - [i142]Nikolaus Demmel, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Bundle Adjustment for Large-Scale Reconstruction. CoRR abs/2103.01843 (2021) - [i141]