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spezial:bib [2019/06/25 15:31] moellenh |
spezial:bib [2020/07/08 14:22] chiotell |
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@STRING{icip = {{P}roceedings of the {IEEE} {I}nternational {C}onference on {I}mage {P}rocessing}} | @STRING{icip = {{P}roceedings of the {IEEE} {I}nternational {C}onference on {I}mage {P}rocessing}} | ||
+ | |||
+ | @STRING{icml = {{I}nternational {C}onference on {M}achine {L}earning (ICML)}} | ||
@STRING{icra = {International Conference on Robotics and Automation (ICRA)}} | @STRING{icra = {International Conference on Robotics and Automation (ICRA)}} | ||
Line 6097: | Line 6099: | ||
titleurl = {rodola-3dv14.pdf}, | titleurl = {rodola-3dv14.pdf}, | ||
topic = {Correspondence, | topic = {Correspondence, | ||
- | } | ||
- | |||
- | @Misc{demmel14, | ||
- | author = Nikolaus Demmel, | ||
- | title = Total Variation Segmentation Incorporating Depth Information | ||
- | month = Sept., | ||
- | year = 2014 | ||
- | note = IDP Project, | ||
- | keywords = Total Variation, Segmentation, | ||
} | } | ||
Line 7822: | Line 7815: | ||
author = "N. Yang and R. Wang and X. Gao and D. Cremers", | author = "N. Yang and R. Wang and X. Gao and D. Cremers", | ||
title = " | title = " | ||
- | journal = "IEEE Robotics and Automation Letters (RA-L)", | + | journal = " |
volume = {3}, | volume = {3}, | ||
issue = {4}, | issue = {4}, | ||
Line 7831: | Line 7824: | ||
titleurl = {yang18challenges.pdf}, | titleurl = {yang18challenges.pdf}, | ||
keywords={Brightness; | keywords={Brightness; | ||
- | note = {{This paper was also selected by IROS' | + | note = {{<a href=" |
} | } | ||
Line 7969: | Line 7962: | ||
} | } | ||
- | @article{Haefner2019A, | + | @inproceedings{sang2020wacv, |
+ | title = {Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach}, | ||
+ | author = {Sang, L. and Haefner, B. and Cremers, D.}, | ||
+ | booktitle={IEEE Winter Conference on Applications of Computer Vision (WACV)}, | ||
+ | month={March}, | ||
+ | address={Colorado, | ||
+ | year = {2020}, | ||
+ | eprint = {1912.06501}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | award = {Spotlight Presentation}, | ||
+ | titleurl = {sang2020wacv.pdf}, | ||
+ | note = { | ||
+ | {<a href="/ | ||
+ | {<a href="/ | ||
+ | }, | ||
+ | } | ||
+ | |||
+ | @article{mukkamala2019arxiv, | ||
+ | title={Bregman Proximal Framework for Deep Linear Neural Networks}, | ||
+ | author={Mahesh Chandra Mukkamala and Felix Westerkamp and Emanuel Laude and Daniel Cremers and Peter Ochs}, | ||
+ | journal = {arXiv preprint arXiv: | ||
+ | year = {2019}, | ||
+ | eprint = {1910.03638}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {math.OC} | ||
+ | } | ||
+ | |||
+ | @article{brahimi2019springer, | ||
+ | title = {On well-posedness of uncalibrated photometric stereo under general lighting}, | ||
+ | author = {Brahimi, M. and Quéau, Y. and Haefner, B. and Cremers, D.}, | ||
+ | journal = {arXiv preprint arXiv: | ||
+ | year = {2019}, | ||
+ | eprint = {1911.07268}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | titleurl = {brahimi2019springer.pdf}, | ||
+ | } | ||
+ | |||
+ | @inproceedings{haefner20193dv, | ||
+ | title = {Photometric Segmentation: | ||
+ | author = {Haefner, B. and Quéau, Y. and Cremers, D.}, | ||
+ | booktitle={International Conference on 3D Vision (3DV)}, | ||
+ | month={September}, | ||
+ | address={Québec City, Canada}, | ||
+ | year = {2019}, | ||
+ | award = {Spotlight Presentation}, | ||
+ | titleurl = {haefner20193dv.pdf}, | ||
+ | note = { | ||
+ | {<a href="/ | ||
+ | }, | ||
+ | } | ||
+ | |||
+ | @inproceedings{haefner2019iccv, | ||
title = {Variational Uncalibrated Photometric Stereo under General Lighting}, | title = {Variational Uncalibrated Photometric Stereo under General Lighting}, | ||
author = {Haefner, B. and Ye, Z. and Gao, M. and Wu, T. and Quéau, Y. and Cremers, D.}, | author = {Haefner, B. and Ye, Z. and Gao, M. and Wu, T. and Quéau, Y. and Cremers, D.}, | ||
- | | + | |
+ | month={October}, | ||
+ | address={Seoul, | ||
eprint = {1904.03942}, | eprint = {1904.03942}, | ||
eprinttype = {arXiv}, | eprinttype = {arXiv}, | ||
Line 7980: | Line 8028: | ||
note = { | note = { | ||
{<a href="/ | {<a href="/ | ||
+ | {<a href="/ | ||
+ | {<a href=" | ||
+ | {<a href=" | ||
+ | {<a href=" | ||
}, | }, | ||
keywords={d-reconstruction, | keywords={d-reconstruction, | ||
Line 7985: | Line 8037: | ||
- | @article{Haefner2018A, | + | @article{laude2019jota, |
+ | title = {Bregman Proximal Mappings and Bregman-Moreau Envelopes under Relative Prox-Regularity}, | ||
+ | | ||
+ | | ||
+ | | ||
+ | year = {2019}, | ||
+ | eprint = {1907.04306}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {math.OC}, | ||
+ | } | ||
+ | |||
+ | @article{haefner2019tpami, | ||
title = {Photometric Depth Super-Resolution}, | title = {Photometric Depth Super-Resolution}, | ||
| | ||
| | ||
year = {2019}, | year = {2019}, | ||
- | | + | eprint = {1809.10097}, |
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | titleurl = {haefner2018.pdf}, | ||
note = { | note = { | ||
{<a href="/ | {<a href="/ | ||
- | {<a href=" | ||
{<a href=" | {<a href=" | ||
+ | {<a href=" | ||
}, | }, | ||
keywords={rgb-d, | keywords={rgb-d, | ||
Line 8000: | Line 8066: | ||
- | @inproceedings{Haefner2018CVPR, | + | @inproceedings{haefner2018cvpr, |
title = {Fight ill-posedness with ill-posedness: | title = {Fight ill-posedness with ill-posedness: | ||
| | ||
Line 8009: | Line 8075: | ||
note = { | note = { | ||
{<a href="/ | {<a href="/ | ||
+ | {<a href="/ | ||
{<a href=" | {<a href=" | ||
{<a href=" | {<a href=" | ||
Line 8018: | Line 8085: | ||
- | @inproceedings{Peng2017, | + | @inproceedings{peng2017, |
title = {Depth Super-Resolution Meets Uncalibrated Photometric Stereo}, | title = {Depth Super-Resolution Meets Uncalibrated Photometric Stereo}, | ||
| | ||
| | ||
year = {2017}, | year = {2017}, | ||
+ | eprint = {1708.00411}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
award = {Oral Presentation at ICCV Workshop on Color and Photometry in Computer Vision}, | award = {Oral Presentation at ICCV Workshop on Color and Photometry in Computer Vision}, | ||
| | ||
Line 8193: | Line 8263: | ||
booktitle = ismrm, | booktitle = ismrm, | ||
keywords = {novelty detection, anomaly detection, machine learning, medical imaging, magnetic resonance imaging, diffusion MRI, segmentation}, | keywords = {novelty detection, anomaly detection, machine learning, medical imaging, magnetic resonance imaging, diffusion MRI, segmentation}, | ||
+ | } | ||
+ | |||
+ | @inproceedings{Vasilev-et-al-2018, | ||
+ | author = {A. Vasilev and V. Golkov and M. Meissner and I. Lipp and E. Sgarlata and V. Tomassini and D. K. Jones and D. Cremers}, | ||
+ | title = {{q}-{S}pace Novelty Detection with Variational Autoencoders}, | ||
+ | year = {2019}, | ||
+ | booktitle = {MICCAI 2019 International Workshop on Computational Diffusion MRI}, | ||
+ | eprint = {1806.02997}, | ||
+ | eprinttype = {arXiv}, | ||
+ | keywords = {deep learning, novelty detection, anomaly detection, neural networks, medical imaging, magnetic resonance imaging, diffusion MRI, deeplearning, | ||
+ | award = {Oral Presentation} | ||
} | } | ||
Line 8220: | Line 8301: | ||
booktitle = {bioRxiv preprint}, | booktitle = {bioRxiv preprint}, | ||
keywords = {precursor microRNA, pre-miRNA, miRNA, deep learning, neural networks, machine learning, deeplearning, | keywords = {precursor microRNA, pre-miRNA, miRNA, deep learning, neural networks, machine learning, deeplearning, | ||
+ | } | ||
+ | |||
+ | @inproceedings{Golkov-et-al-2020-ROC, | ||
+ | author = {V. Golkov and A. Becker and D. T. Plop and D. \v{C}uturilo and N. Davoudi and J. Mendenhall and R. Moretti and J. Meiler and D. Cremers}, | ||
+ | title = {Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions}, | ||
+ | year = {2020}, | ||
+ | % howpublished = {Preprint}, | ||
+ | note = {{<a href=" | ||
+ | booktitle = {bioRxiv preprint}, | ||
+ | keywords = {deep learning, drug discovery, virtual screening, neural networks, machine learning, QSAR, classification, | ||
} | } | ||
Line 8343: | Line 8434: | ||
} | } | ||
+ | @InProceedings{schubert2019vidsors, | ||
+ | author = "D. Schubert and N. Demmel and L. von Stumberg and V. Usenko and D. Cremers", | ||
+ | title = " | ||
+ | booktitle = iros, | ||
+ | year = " | ||
+ | month = " | ||
+ | arXiv = " | ||
+ | note = {{<a href=" | ||
+ | keywords = vidsors | ||
+ | } | ||
Line 8363: | Line 8464: | ||
year={2010}, | year={2010}, | ||
organization={IEEE} | organization={IEEE} | ||
- | } | ||
- | |||
- | @article{Vasilev-et-al-2018, | ||
- | author = {A. Vasilev and V. Golkov and M. Meissner and I. Lipp and E. Sgarlata and V. Tomassini and D. K. Jones and D. Cremers}, | ||
- | title = {{q}-{S}pace Novelty Detection with Variational Autoencoders}, | ||
- | year = {2018}, | ||
- | journal = {arXiv preprint arXiv: | ||
- | eprint = {1806.02997}, | ||
- | eprinttype = {arXiv}, | ||
- | keywords = {deep learning, novelty detection, anomaly detection, neural networks, medical imaging, magnetic resonance imaging, diffusion MRI, deeplearning, | ||
} | } | ||
Line 8385: | Line 8476: | ||
} | } | ||
- | @article{eisenberger2019divfree, | + | @InProceedings{eisenberger2019divfree, |
author = "M. Eisenberger and Z. L\" | author = "M. Eisenberger and Z. L\" | ||
title = " | title = " | ||
- | | + | |
arXiv = " arXiv: | arXiv = " arXiv: | ||
year = " | year = " | ||
month = " | month = " | ||
- | note = {Will be presented at Symposium on Geometry Processing (SGP) {<a href=" | + | note = {{<a href=" |
} | } | ||
Line 8449: | Line 8540: | ||
} | } | ||
- | @InProceedings{sundermeyer2018eccv, | + | @InProceedings{sundermeyer18implicit, |
author = {M. Sundermeyer and Z. Marton and M. Durner and M. Brucker and R. Triebel}, | author = {M. Sundermeyer and Z. Marton and M. Durner and M. Brucker and R. Triebel}, | ||
title = {Implicit 3D Orientation Learning for 6D Object Detection from RGB Images}, | title = {Implicit 3D Orientation Learning for 6D Object Detection from RGB Images}, | ||
Line 8458: | Line 8549: | ||
} | } | ||
- | @InProceedings{denninger18iros, | + | @InProceedings{denninger18persistent, |
author = {M. Denninger and R. Triebel}, | author = {M. Denninger and R. Triebel}, | ||
title = {Persistent Anytime Learning of Objects from Unseen Classes }, | title = {Persistent Anytime Learning of Objects from Unseen Classes }, | ||
Line 8467: | Line 8558: | ||
award = {Best Cognitive Robotics Paper Finalist}, | award = {Best Cognitive Robotics Paper Finalist}, | ||
} | } | ||
- | @InProceedings{grixa18iros, | + | @InProceedings{grixa18appearance, |
author = {I. Grixa and P. Schulz and W. St\" | author = {I. Grixa and P. Schulz and W. St\" | ||
title = {Appearance-Based Along-Route Localization for Planetary Missions}, | title = {Appearance-Based Along-Route Localization for Planetary Missions}, | ||
Line 8529: | Line 8620: | ||
title = {{Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs}}, | title = {{Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs}}, | ||
year = {2018}, | year = {2018}, | ||
- | note = {{<a href=" | + | note = {{<a href=" |
} | } | ||
Line 8590: | Line 8681: | ||
titleurl = {moellenh-cvpr-19.pdf}, | titleurl = {moellenh-cvpr-19.pdf}, | ||
award = {Oral Presentation}, | award = {Oral Presentation}, | ||
- | note = {{<a href=" | + | note = {{<a href=" |
} | } | ||
- | @article{moeller-et-al-19, | + | @article{usenko19nfr, |
- | author = "M. Moeller and T. M{\" | + | |
- | title = " | + | |
- | journal = {preprint}, | + | |
- | year = " | + | |
- | note = {{<a href=" | + | |
- | } | + | |
- | + | ||
- | @InProceedings{usenko19nfr, | + | |
author = "V. Usenko and N. Demmel and D. Schubert and J. Stueckler and D. Cremers", | author = "V. Usenko and N. Demmel and D. Schubert and J. Stueckler and D. Cremers", | ||
title = " | title = " | ||
- | | + | |
- | | + | |
- | | + | |
- | | + | |
- | | + | number={2}, |
+ | pages={422-429}, | ||
+ | keywords={Simultaneous localization and mapping; | ||
+ | doi={10.1109/ | ||
+ | | ||
keywords = nfr | keywords = nfr | ||
} | } | ||
Line 8626: | Line 8713: | ||
} | } | ||
- | @article{wang19DirectShape, | + | @InProceedings{wang2020directshape, |
- | author = "R. Wang and N. Yang and J. Stueckler and D. Cremers", | + | author={R. Wang and N. Yang and J. Stueckler and D. Cremers}, |
- | title = "DirectShape: | + | title={DirectShape: |
- | | + | |
- | year = " | + | year={2020}, |
- | note = {{<a href=" | + | note={{< |
- | keywords = {stereo, 3D reconstruction, | + | keywords={stereo, |
+ | } | ||
+ | |||
+ | @inproceedings{du2020dh3d, | ||
+ | author = "J. Du and R. Wang and D. Cremers", | ||
+ | title = "DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization", | ||
+ | booktitle = " | ||
+ | year = " | ||
+ | award = {Spotlight Presentation}, | ||
+ | keywords={SLAM, | ||
} | } | ||
Line 8652: | Line 8748: | ||
year = " | year = " | ||
note = {{<a href=" | note = {{<a href=" | ||
- | award = {Full Oral Presentation} | + | award = {Full Oral Presentation}, |
+ | month={6} | ||
} | } | ||
Line 8663: | Line 8760: | ||
} | } | ||
- | @article{gn-net-19, | + | @article{gn-net-2020, |
author = "L. von Stumberg and P. Wenzel and Q. Khan and D. Cremers", | author = "L. von Stumberg and P. Wenzel and Q. Khan and D. Cremers", | ||
- | title = " | + | title = " |
- | journal = {preprint}, | + | journal = {IEEE Robotics and Automation Letters (RA-L) & International Conference on Robotics and Automation (ICRA)}, |
- | year = "2019", | + | year = "2020", |
- | note = {{<a href=" | + | volume={5}, |
+ | number={2}, | ||
+ | pages={890-897}, | ||
+ | note = {{<a href=" | ||
keywords = {gn-net} | keywords = {gn-net} | ||
} | } | ||
- | @article{eisenberger2019smoothshells, | + | @inproceedings{eisenberger2019smoothshells, |
author = "M. Eisenberger and Z. L\" | author = "M. Eisenberger and Z. L\" | ||
title = " | title = " | ||
- | | + | |
+ | year = " | ||
+ | award = {Oral Presentation}, | ||
+ | note = {<a href=" | ||
+ | } | ||
+ | |||
+ | @inproceedings{eisenberger2020hamiltonian, | ||
+ | author = "M. Eisenberger and D. Cremers", | ||
+ | title = " | ||
+ | booktitle = " | ||
+ | year = " | ||
+ | award = {Spotlight Presentation}, | ||
+ | note = {<a href=" | ||
+ | } | ||
+ | |||
+ | @inproceedings{Weiss-et-al-cvpr2020, | ||
+ | author = "S. Weiss and R. Maier and D. Cremers and R. Westermann and N. Thuerey", | ||
+ | title = " | ||
+ | booktitle = "IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)", | ||
+ | year = " | ||
+ | titleurl = {Weiss_et_al_cvpr2020.pdf}, | ||
+ | } | ||
+ | |||
+ | @inproceedings{control-across-weathers-19, | ||
+ | author = "Q. Khan and P. Wenzel and D. Cremers and L. Leal-Taixe", | ||
+ | title = " | ||
+ | booktitle | ||
year = " | year = " | ||
- | note = {{<a href=" | + | note = {{<a href=" |
} | } | ||
+ | |||
+ | @InProceedings{puang19visual, | ||
+ | title = {{Visual Repetition Sampling for Robot Manipulation Planning}}, | ||
+ | author = {E.Y. Puang and P. Lehner and Z.C. Marton and M. Durner and R. Triebel and A. Albu-Sch\" | ||
+ | booktitle = icra, | ||
+ | year = {2019} | ||
+ | } | ||
+ | |||
+ | @inproceedings{moeller-et-al-19, | ||
+ | author = "M. Moeller and T. M{\" | ||
+ | title = " | ||
+ | booktitle={International Conference on Computer Vision (ICCV)}, | ||
+ | year = " | ||
+ | month= {10}, | ||
+ | address={Seoul, | ||
+ | eprint = {1904.03081}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | } | ||
+ | |||
+ | @inproceedings{jung2019corl, | ||
+ | author = {E. Jung and N. Yang and D. Cremers}, | ||
+ | booktitle = {Conference on Robot Learning (CoRL)}, | ||
+ | title = {{Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light}}, | ||
+ | award = {Full Oral Presentation}, | ||
+ | note = {{<a href=" | ||
+ | year = {2019} | ||
+ | } | ||
+ | |||
+ | @inproceedings{weiss2019sparse, | ||
+ | title={Sparse Surface Constraints for Combining Physics-based Elasticity Simulation and Correspondence-Free Object Reconstruction}, | ||
+ | author={S. Weiss and R. Maier and R. Westermann and D. Cremers and N. Thuerey}, | ||
+ | journal = {preprint}, | ||
+ | booktitle = {arXiv preprint arXiv: | ||
+ | year={2019}, | ||
+ | eprint = {1910.01812}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | note = {{<a href=" | ||
+ | } | ||
+ | |||
+ | @article{Della-Libera-et-al-2019, | ||
+ | author = {L. Della Libera and V. Golkov and Y. Zhu and A. Mielke and D. Cremers}, | ||
+ | title = {Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods}, | ||
+ | year = {2019}, | ||
+ | journal = {arXiv preprint arXiv: | ||
+ | eprint = {1910.14594}, | ||
+ | eprinttype = {arXiv}, | ||
+ | keywords = {deep learning, neural networks, 2D, 3D, rotations, invariance, equivariance, | ||
+ | } | ||
+ | |||
+ | @InBook{vi-dso-chapter, | ||
+ | author = "L. von Stumberg and V. Usenko and D. Cremers", | ||
+ | title = "A Review and Quantitative Evaluation of Direct Visual–Inertial Odometry", | ||
+ | editor = "M. Yang and B. Rosenhahn and V. Murino", | ||
+ | chapter = " | ||
+ | publisher = " | ||
+ | pages = " | ||
+ | year = " | ||
+ | doi = " | ||
+ | isbn = " | ||
+ | } | ||
+ | |||
+ | @Inbook{usenko2020_tumflyers, | ||
+ | author=" | ||
+ | editor=" | ||
+ | title=" | ||
+ | chapter=" | ||
+ | year=" | ||
+ | publisher=" | ||
+ | address=" | ||
+ | pages=" | ||
+ | isbn=" | ||
+ | doi=" | ||
+ | } | ||
+ | |||
+ | |||
+ | @InProceedings{sommer19spline, | ||
+ | author = "C. Sommer and V. Usenko and D. Schubert and N. Demmel and D. Cremers", | ||
+ | title = " | ||
+ | eprint = {1911.08860}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | booktitle=cvpr, | ||
+ | year = {2020}, | ||
+ | award = {Oral Presentation}, | ||
+ | keywords=lie-spline | ||
+ | } | ||
+ | |||
+ | @inproceedings{brechet2019, | ||
+ | title = {Informative GANs via Structured Regularization of Optimal Transport}, | ||
+ | | ||
+ | | ||
+ | year = {2019}, | ||
+ | | ||
+ | | ||
+ | | ||
+ | } | ||
+ | |||
+ | @InProceedings{yang20d3vo, | ||
+ | author = "N. Yang and L. von Stumberg and R. Wang and D. Cremers", | ||
+ | title = "D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry", | ||
+ | booktitle=cvpr, | ||
+ | year = {2020}, | ||
+ | eprint = {2003.01060}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {cs.CV}, | ||
+ | award = {Oral Presentation}, | ||
+ | keywords = {dso,dvso, deep learning, deeplearning, | ||
+ | } | ||
+ | |||
+ | @InProceedings{fontan20information, | ||
+ | author | ||
+ | title = " | ||
+ | booktitle=cvpr, | ||
+ | year=2020, | ||
+ | award = {Oral Presentation}, | ||
+ | } | ||
+ | |||
+ | @InProceedings{sundermeyer20multi, | ||
+ | author | ||
+ | title = " | ||
+ | booktitle=cvpr, | ||
+ | year=2020, | ||
+ | } | ||
+ | |||
+ | @InProceedings{wenger20nonparametric, | ||
+ | author = "J. Wenger and H. Kjellstr\" | ||
+ | title = " | ||
+ | booktitle = {International Conference on Artificial | ||
+ | Intelligence and Statistics (AISTATS)}, | ||
+ | year = {2020}, | ||
+ | } | ||
+ | |||
+ | @InProceedings{lee20visual, | ||
+ | author = " J. Lee and R. Balachandran and Y. Sarkisov and M. De Stefano and A. Coelho and K. Shinde and M. J. Kim and R. Triebel and K. Kondak", | ||
+ | title = " | ||
+ | booktitle = icra, | ||
+ | year = {2020}, | ||
+ | } | ||
+ | |||
+ | @InProceedings{steidle19visual, | ||
+ | author = "F. Steidle and W. St\" | ||
+ | title = " | ||
+ | booktitle = " 11th International Micro Air Vehicle Competition and Conference (IMAV)", | ||
+ | year = {2019}, | ||
+ | } | ||
+ | | ||
+ | |||
+ | @InProceedings{feng19introspective, | ||
+ | author = "J. Feng and M. Durner and Z.-C. Marton and F. Balint-Benczedi and R. Triebel", | ||
+ | title = " | ||
+ | booktitle = " | ||
+ | year = {2019} | ||
+ | } | ||
+ | | ||
+ | | ||
+ | | ||
+ | @ARTICLE{giubilato20relocalization, | ||
+ | author = { R. Giubilato and M. Vayugundla and M. Schuster and W. St\" | ||
+ | title = {Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras}, | ||
+ | journal = "IEEE Robotics and Automation Letters", | ||
+ | volume = " | ||
+ | number = " | ||
+ | pages = " 580--587", | ||
+ | year = {2020}, | ||
+ | } | ||
+ | |||
+ | @ARTICLE{sundermeyer19augmented, | ||
+ | author={ M. Sundermeyer and Z. Marton and M. Durner and R. Triebel}, | ||
+ | title={Augmented Autoencoders: | ||
+ | journal=ijcv, | ||
+ | year={2019}, | ||
+ | } | ||
+ | |||
+ | @ARTICLE{lutz20ardea, | ||
+ | author={P. Lutz and M. G. M\" | ||
+ | title = {ARDEA—An MAV with skills for future planetary missions}, | ||
+ | journal={Journal of Field Robotics (JFR)}, | ||
+ | year={2020} | ||
+ | } | ||
+ | |||
+ | @inproceedings{ye2020optimization, | ||
+ | author = "Z. Ye and T. M\" | ||
+ | title = " | ||
+ | booktitle = {International Conference on Artificial | ||
+ | Intelligence and Statistics (AISTATS)}, | ||
+ | year = {2020}, | ||
+ | titleurl = {ye-et-al-combinatorial-20.pdf}, | ||
+ | note = { | ||
+ | {<a href=" | ||
+ | }, | ||
+ | } | ||
+ | |||
+ | @phdthesis{maier2020dissertation, | ||
+ | author={R. Maier}, | ||
+ | title={High-Quality {3D} Reconstruction from Low-Cost {RGB-D} Sensors}, | ||
+ | type={Dissertation}, | ||
+ | school={Technische Universit\" | ||
+ | address={M\" | ||
+ | year={2020} | ||
+ | } | ||
+ | |||
+ | @inbook{maier2020rgbdvision, | ||
+ | title={{RGB-D Vision}}, | ||
+ | author={R. Maier and D. Cremers}, | ||
+ | chapter={Encyclopedia of Robotics}, | ||
+ | editor={Ang, | ||
+ | year={2020}, | ||
+ | publisher={Springer Berlin Heidelberg}, | ||
+ | address={Berlin, | ||
+ | pages={1--11}, | ||
+ | isbn={978-3-642-41610-1}, | ||
+ | doi={10.1007/ | ||
+ | url={https:// | ||
+ | } | ||
+ | |||
+ | @Inbook{Moeller2018, | ||
+ | author=" | ||
+ | and Cremers, Daniel", | ||
+ | editor=" | ||
+ | title=" | ||
+ | bookTitle=" | ||
+ | year=" | ||
+ | publisher=" | ||
+ | address=" | ||
+ | pages=" | ||
+ | titleurl = {moeller_cremers2020_denoising_old_and_new.pdf}, | ||
+ | } | ||
+ | |||
+ | |||
+ | |||
+ | @inproceedings{lee2020estimating, | ||
+ | author = " | ||
+ | title = " | ||
+ | booktitle = icml, | ||
+ | year = {2020} | ||
+ | } | ||
+ | |||
+ | @article{liu2020effective, | ||
+ | title={Effective Version Space Reduction for Convolutional Neural Networks}, | ||
+ | author={Liu, | ||
+ | journal={arXiv preprint arXiv: | ||
+ | year={2020}, | ||
+ | booktitle={European Conference on Machine Learning and Data Mining (ECML-PKDD)}, | ||
+ | note={{< | ||
+ | } | ||
+ | |||
+ |