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ORCIDDaniel Cremers
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- affiliation: Technical University Munich, Germany
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2020 – today
- 2022
[i158]Lukas von Stumberg, Daniel Cremers:
DM-VIO: Delayed Marginalization Visual-Inertial Odometry. CoRR abs/2201.04114 (2022)- [i157]Qing Cheng, Niclas Zeller, Daniel Cremers:
Vision-based Large-scale 3D Semantic Mapping for Autonomous Driving Applications. CoRR abs/2203.01087 (2022) - [i156]Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner:
Intrinsic Neural Fields: Learning Functions on Manifolds. CoRR abs/2203.07967 (2022) - [i155]Florian Müller, Qadeer Khan, Daniel Cremers:
Lateral Ego-Vehicle Control without Supervision using Point Clouds. CoRR abs/2203.10662 (2022) - [i154]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) - [i153]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) - [i152]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) - [i151]Abhishek Saroha, Marvin Eisenberger, Tarun Yenamandra, Daniel Cremers:
Implicit Shape Completion via Adversarial Shape Priors. CoRR abs/2204.10060 (2022) - [i150]Paul Roetzer, Paul Swoboda, Daniel Cremers, Florian Bernard:
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching. CoRR abs/2204.12805 (2022) - [i149]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Power Bundle Adjustment for Large-Scale 3D Reconstruction. CoRR abs/2204.12834 (2022) - [i148]Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers:
Neural Implicit Representations for Physical Parameter Inference from a Single Video. CoRR abs/2204.14030 (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, Bo Chen, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixé, Maxwell D. Collins:
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]Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers:
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. CoRR abs/2103.04727 (2021) - [i140]Qadeer Khan, Patrick Wenzel, Daniel Cremers:
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry. CoRR abs/2103.11204 (2021) - [i139]Zhenzhang Ye, Tarun Yenamandra, Florian Bernard, Daniel Cremers:
Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections. CoRR abs/2103.17229 (2021) - [i138]Marvin Eisenberger, David Novotný, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers, Andrea Vedaldi:
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go. CoRR abs/2106.09431 (2021) - [i137]Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixé, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen:
DeepLab2: A TensorFlow Library for Deep Labeling. CoRR abs/2106.09748 (2021) - [i136]Jason Chui, Simon Klenk, Daniel Cremers:
Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization. CoRR abs/2107.04536 (2021) - [i135]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. CoRR abs/2107.06028 (2021) - [i134]Yu Wang, Yuesong Shen, Daniel Cremers:
Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classification. CoRR abs/2107.13059 (2021) - [i133]Simon Klenk, Jason Chui, Nikolaus Demmel, Daniel Cremers:
TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset. CoRR abs/2108.07329 (2021) - [i132]Ji Yang, Lu Sang, Daniel Cremers:
Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry. CoRR abs/2109.01461 (2021) - [i131]Nikolaus Demmel, David Schubert, Christiane Sommer, Daniel Cremers, Vladyslav Usenko:
Square Root Marginalization for Sliding-Window Bundle Adjustment. CoRR abs/2109.02182 (2021) - [i130]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. CoRR abs/2109.05509 (2021) - [i129]Maximilian Mozes, Martin Schmitt, Vladimir Golkov, Hinrich Schütze, Daniel Cremers:
Scene Graph Generation for Better Image Captioning? CoRR abs/2109.11398 (2021) - [i128]Florian Bernard, Daniel Cremers, Johan Thunberg:
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation. CoRR abs/2110.00053 (2021) - [i127]Simon Weber, Nikolaus Demmel, Daniel Cremers:
Multidirectional Conjugate Gradients for Scalable Bundle Adjustment. CoRR abs/2110.04015 (2021) - [i126]Lukas Koestler, Nan Yang, Niclas Zeller, Daniel Cremers:
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo. CoRR abs/2111.07418 (2021) - [i125]Christiane Sommer, Lu Sang, David Schubert, Daniel Cremers:
Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction. CoRR abs/2111.13652 (2021) - [i124]Viktoria Ehm, Daniel Cremers, Florian Bernard:
Shortest Paths in Graphs with Matrix-Valued Edges: Concepts, Algorithm and Application to 3D Multi-Shape Analysis. CoRR abs/2112.04165 (2021) - 2020
- [j83]Emanuel Laude, Peter Ochs, Daniel Cremers:
Bregman Proximal Mappings and Bregman-Moreau Envelopes Under Relative Prox-Regularity. J. Optim. Theory Appl. 184(3): 724-761 (2020) - [j82]Bjoern Haefner, Songyou Peng, Alok Verma, Yvain Quéau, Daniel Cremers:
Photometric Depth Super-Resolution. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2453-2464 (2020) - [j81]Vladyslav Usenko, Nikolaus Demmel, David Schubert, Jörg Stückler, Daniel Cremers:
Visual-Inertial Mapping With Non-Linear Factor Recovery. IEEE Robotics Autom. Lett. 5(2): 422-429 (2020) - [j80]Lukas von Stumberg, Patrick Wenzel, Qadeer Khan, Daniel Cremers:
GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization. IEEE Robotics Autom. Lett. 5(2): 890-897 (2020) - [j79]Christiane Sommer, Yumin Sun, Leonidas J. Guibas, Daniel Cremers, Tolga Birdal:
From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds. IEEE Robotics Autom. Lett. 5(2): 1764-1771 (2020) - [c284]Nikolaus Demmel, Maolin Gao, Emanuel Laude, Tao Wu, Daniel Cremers:
Distributed Photometric Bundle Adjustment. 3DV 2020: 140-149 - [c283]Benjamin Holzschuh, Zorah Lähner, Daniel Cremers:
Simulated Annealing for 3D Shape Correspondence. 3DV 2020: 252-260 - [c282]Mehmet Aygün, Zorah Lähner, Daniel Cremers:
Unsupervised Dense Shape Correspondence using Heat Kernels. 3DV 2020: 573-582 - [c281]Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers:
3D Deep Learning for Biological Function Prediction from Physical Fields. 3DV 2020: 928-937 - [c280]Lukas von Stumberg, Patrick Wenzel, Nan Yang, Daniel Cremers:
LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization. 3DV 2020: 968-977 - [c279]Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers:
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. AISTATS 2020: 657-668 - [c278]Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers:
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry. CVPR 2020: 1278-1289 - [c277]Thomas Frerix, Matthias Nießner, Daniel Cremers:
Homogeneous Linear Inequality Constraints for Neural Network Activations. CVPR Workshops 2020: 3229-3234 - [c276]Sebastian Weiss, Robert Maier, Daniel Cremers, Rüdiger Westermann, Nils Thuerey:
Correspondence-Free Material Reconstruction using Sparse Surface Constraints. CVPR 2020: 4685-4694 - [c275]Christiane Sommer, Vladyslav Usenko, David Schubert, Nikolaus Demmel, Daniel Cremers:
Efficient Derivative Computation for Cumulative B-Splines on Lie Groups. CVPR 2020: 11145-11153 - [c274]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Smooth Shells: Multi-Scale Shape Registration With Functional Maps. CVPR 2020: 12262-12271 - [c273]Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers:
Learning Monocular 3D Vehicle Detection Without 3D Bounding Box Labels. GCPR 2020: 116-129 - [c272]Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving. GCPR 2020: 404-417 - [c271]Marvin Eisenberger, Daniel Cremers:
Hamiltonian Dynamics for Real-World Shape Interpolation. ECCV (4) 2020: 179-196 - [c270]Juan Du, Rui Wang, Daniel Cremers:
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization. ECCV (4) 2020: 744-762 - [c269]Christiane Sommer, Yumin Sun, Erik Bylow, Daniel Cremers:
PrimiTect: Fast Continuous Hough Voting for Primitive Detection. ICRA 2020: 8404-8410 - [c268]Rui Wang, Nan Yang, Jörg Stückler, Daniel Cremers:
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation. ICRA 2020: 11067-11073 - [c267]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport. NeurIPS 2020 - [c266]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. ECML/PKDD (2) 2020: 85-100 - [c265]Lu Sang, Bjoern Haefner, Daniel Cremers:
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach. WACV 2020: 1-10 - [p8]Vladyslav Usenko, Lukas von Stumberg, Jörg Stückler, Daniel Cremers:
TUM Flyers: Vision - Based MAV Navigation for Systematic Inspection of Structures. EuRoC 2020: 189-209 - [i123]Christiane Sommer, Yumin Sun, Leonidas J. Guibas, Daniel Cremers, Tolga Birdal:
From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds. CoRR abs/2001.07360 (2020) - [i122]Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Learn to Predict Sets Using Feed-Forward Neural Networks. CoRR abs/2001.11845 (2020) - [i121]Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers:
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. CoRR abs/2002.12236 (2020) - [i120]Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers:
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry. CoRR abs/2003.01060 (2020) - [i119]Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé:
MOT20: A benchmark for multi object tracking in crowded scenes. CoRR abs/2003.09003 (2020) - [i118]Marvin Eisenberger, Daniel Cremers:
Hamiltonian Dynamics for Real-World Shape Interpolation. CoRR abs/2004.05199 (2020) - [i117]Christiane Sommer, Yumin Sun, Erik Bylow, Daniel Cremers:
PrimiTect: Fast Continuous Hough Voting for Primitive Detection. CoRR abs/2005.07457 (2020) - [i116]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. CoRR abs/2006.12456 (2020) - [i115]Yuesong Shen, Daniel Cremers:
Deriving Neural Network Design and Learning from the Probabilistic Framework of Chain Graphs. CoRR abs/2006.16856 (2020) - [i114]Vladimir Golkov, Alexander Becker, Daniel T. Plop, Daniel Cuturilo, Neda Davoudi, Jeffrey L. Mendenhall, Rocco Moretti, Jens Meiler, Daniel Cremers:
Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions. CoRR abs/2007.07029 (2020) - [i113]Juan Du, Rui Wang, Daniel Cremers:
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization. CoRR abs/2007.09217 (2020) - [i112]Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving. CoRR abs/2009.06364 (2020) - [i111]Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers:
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels. CoRR abs/2010.03506 (2020) - [i110]Lukas von Stumberg, Patrick Wenzel, Nan Yang, Daniel Cremers:
LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization. CoRR abs/2010.06323 (2020) - [i109]Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian D. Reid, Stefan Roth, Laura Leal-Taixé:
MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking. CoRR abs/2010.07548 (2020) - [i108]Mehmet Aygün, Zorah Lähner, Daniel Cremers:
Unsupervised Dense Shape Correspondence using Heat Kernels. CoRR abs/2010.12682 (2020) - [i107]Giorgio Fabbro, Vladimir Golkov, Thomas Kemp, Daniel Cremers:
Speech Synthesis and Control Using Differentiable DSP. CoRR abs/2010.15084 (2020) - [i106]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport. CoRR abs/2010.15261 (2020) - [i105]Felix Wimbauer, Nan Yang, Lukas von Stumberg, Niclas Zeller, Daniel Cremers:
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera. CoRR abs/2011.11814 (2020) - [i104]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. CoRR abs/2011.12430 (2020) - [i103]Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. CoRR abs/2011.13076 (2020) - [i102]Tarun Yenamandra, Ayush Tewari, Florian Bernard, Hans-Peter Seidel, Mohamed Elgharib, Daniel Cremers, Christian Theobalt:
i3DMM: Deep Implicit 3D Morphable Model of Human Heads. CoRR abs/2011.14143 (2020) - [i101]Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard:
Isometric Multi-Shape Matching. CoRR abs/2012.02689 (2020) - [i100]Ioannis Chiotellis, Daniel Cremers:
Neural Online Graph Exploration. CoRR abs/2012.03345 (2020) - [i99]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-hoc Uncertainty Calibration for Domain Drift Scenarios. CoRR abs/2012.10988 (2020)
2010 – 2019
- 2019
- [j78]Marvin Eisenberger, Zorah Lähner, Daniel Cremers:
Divergence-Free Shape Correspondence by Deformation. Comput. Graph. Forum 38(5): 1-12 (2019) - [j77]Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
Video Object Segmentation without Temporal Information. IEEE Trans. Pattern Anal. Mach. Intell. 41(6): 1515-1530 (2019) - [j76]Henning Tjaden, Ulrich Schwanecke, Elmar Schömer, Daniel Cremers:
A Region-Based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 41(8): 1797-1812 (2019) - [c264]Bjoern Haefner, Yvain Quéau, Daniel Cremers:
Photometric Segmentation: Simultaneous Photometric Stereo and Masking. 3DV 2019: 222-229 - [c263]Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, Jingyu Yang:
Shape Correspondence with Isometric and Non-Isometric Deformations. 3DOR@Eurographics 2019: 111-119 - [c262]Emanuel Laude, Tao Wu, Daniel Cremers:
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems. AISTATS 2019: 547-556 - [c261]Eunah Jung, Nan Yang, Daniel Cremers:
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light. CoRL 2019: 651-660 - [c260]Thomas Möllenhoff, Daniel Cremers:
Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus. CVPR 2019: 11117-11126 - [c259]Michael Möller, Thomas Möllenhoff, Daniel Cremers:
Controlling Neural Networks via Energy Dissipation. ICCV 2019: 3255-3264 - [c258]Zhenzhang Ye, Bjoern Haefner, Maolin Gao, Tao Wu, Yvain Quéau, Daniel Cremers:
Variational Uncalibrated Photometric Stereo Under General Lighting. ICCV 2019: 8538-8547 - [c257]Thomas Möllenhoff, Daniel Cremers:
Flat Metric Minimization with Applications in Generative Modeling. ICML 2019: 4626-4635 - [c256]David Schubert, Nikolaus Demmel, Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers:
Rolling-Shutter Modelling for Direct Visual-Inertial Odometry. IROS 2019: 2462-2469 - [c255]Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé:
Towards Generalizing Sensorimotor Control Across Weather Conditions. IROS 2019: 4497-4503 - [i98]