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Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration

Feb 24, 2021
Christian Tomani, Daniel Cremers, Florian Buettner

* Technical report 

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STEP: Segmenting and Tracking Every Pixel

Feb 23, 2021
Mark Weber, Jun Xie, Maxwell Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixe, Liang-Chieh Chen

* Datasets, metric, and baselines will be made publicly available soon 

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Variational Data Assimilation with a Learned Inverse Observation Operator

Feb 22, 2021
Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer


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Rotation-Equivariant Deep Learning for Diffusion MRI

Feb 13, 2021
Philip MĂĽller, Vladimir Golkov, Valentina Tomassini, Daniel Cremers

* 24 pages, 8 figures 

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Tight Integration of Feature-Based Relocalization in Monocular Direct Visual Odometry

Feb 08, 2021
Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers

* A typo in the title is corrected 

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Tight-Integration of Feature-Based Relocalization in Monocular Direct Visual Odometry

Feb 01, 2021
Mariia Gladkova, Rui Wang, Niclas Zeller, Daniel Cremers


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Post-hoc Uncertainty Calibration for Domain Drift Scenarios

Dec 20, 2020
Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner

* Technical report 

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Neural Online Graph Exploration

Dec 06, 2020
Ioannis Chiotellis, Daniel Cremers


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Isometric Multi-Shape Matching

Dec 04, 2020
Maolin Gao, Zorah Lähner, Johan Thunberg, Daniel Cremers, Florian Bernard


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i3DMM: Deep Implicit 3D Morphable Model of Human Heads

Nov 28, 2020
Tarun Yenamandra, Ayush Tewari, Florian Bernard, Hans-Peter Seidel, Mohamed Elgharib, Daniel Cremers, Christian Theobalt

* Project page: http://gvv.mpi-inf.mpg.de/projects/i3DMM/ 

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Non-Rigid Puzzles

Nov 26, 2020
Or Litany, Emanuele RodolĂ , Alex Bronstein, Michael Bronstein, Daniel Cremers

* Computer Graphics Forum, Volume 35, Issue 5, August 2016 

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SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition

Nov 24, 2020
Yan Xia, Yusheng Xu, Shuang Li, Rui Wang, Juan Du, Daniel Cremers, Uwe Stilla

* 10 pages, 7 figures, 6 tables 

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MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Nov 24, 2020
Felix Wimbauer, Nan Yang, Lukas von Stumberg, Niclas Zeller, Daniel Cremers

* Project page with video can be found under https://vision.in.tum.de/research/monorec . 14 pages, 10 figures, 5 tables 

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Deep Shells: Unsupervised Shape Correspondence with Optimal Transport

Oct 28, 2020
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers


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Unsupervised Dense Shape Correspondence using Heat Kernels

Oct 23, 2020
Mehmet Aygün, Zorah Lähner, Daniel Cremers

* In International Conference on 3D Vision (3DV), 2020 

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MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking

Oct 15, 2020
Patrick Dendorfer, Aljoša Ošep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian Reid, Stefan Roth, Laura Leal-Taixé

* Accepted at IJCV 

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LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization

Oct 13, 2020
Lukas von Stumberg, Patrick Wenzel, Nan Yang, Daniel Cremers

* International Conference on 3D Vision (3DV), 2020 

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4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving

Sep 14, 2020
Patrick Wenzel, Rui Wang, Nan Yang, Qing Cheng, Qadeer Khan, Lukas von Stumberg, Niclas Zeller, Daniel Cremers

* German Conference on Pattern Recognition (GCPR 2020) 

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DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization

Jul 17, 2020
Juan Du, Rui Wang, Daniel Cremers

* ECCV 2020, sportlight 

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Deriving Neural Network Design and Learning from the Probabilistic Framework of Chain Graphs

Jun 30, 2020
Yuesong Shen, Daniel Cremers


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Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions

Jun 25, 2020
Vladimir Golkov, Alexander Becker, Daniel T. Plop, Daniel ÄŚuturilo, Neda Davoudi, Jeffrey Mendenhall, Rocco Moretti, Jens Meiler, Daniel Cremers

* 10 pages 

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Effective Version Space Reduction for Convolutional Neural Networks

Jun 22, 2020
Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers

* 22 pages, 8 figures, to be published in the Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2020 

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PrimiTect: Fast Continuous Hough Voting for Primitive Detection

May 15, 2020
Christiane Sommer, Yumin Sun, Erik Bylow, Daniel Cremers

* Accepted to IEEE International Conference on Robotics and Automation (ICRA), 2020 | Code: https://github.com/c-sommer/primitect 

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Hamiltonian Dynamics for Real-World Shape Interpolation

Apr 10, 2020
Marvin Eisenberger, Daniel Cremers


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D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry

Mar 28, 2020
Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers

* CVPR 2020 

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MOT20: A benchmark for multi object tracking in crowded scenes

Mar 19, 2020
Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé

* The sequences of the new MOT20 benchmark were previously presented in the CVPR 2019 tracking challenge ( arXiv:1906.04567 ). The differences between the two challenges are: - New and corrected annotations - New sequences, as we had to crop and transform some old sequences to achieve higher quality in the annotations. - New baselines evaluations and different sets of public detections 

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Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning

Feb 27, 2020
Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers

* Presented at the 23 rd International Conference on Artificial Intelligence and Statistics (AISTATS) 2020. Code: https://github.com/zhenzhangye/graph_TV_recond 

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Learn to Predict Sets Using Feed-Forward Neural Networks

Jan 30, 2020
Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian Reid

* arXiv admin note: substantial text overlap with arXiv:1805.00613 

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From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds

Jan 21, 2020
Christiane Sommer, Yumin Sun, Leonidas Guibas, Daniel Cremers, Tolga Birdal

* Accepted to IEEE Robotics and Automation Letters 2020 | Video: https://youtu.be/nHWJrA6RcB0 | Code: https://github.com/c-sommer/orthogonal-planes 

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