BibTeX records: Nikolaus Mayer

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@phdthesis{DBLP:phd/dnb/Mayer20a,
  author       = {Nikolaus Mayer},
  title        = {Synthetic training data for deep neural networks on visual correspondence
                  tasks},
  school       = {University of Freiburg, Freiburg im Breisgau, Germany},
  year         = {2020},
  url          = {https://freidok.uni-freiburg.de/data/166944},
  urn          = {urn:nbn:de:bsz:25-freidok-1669440},
  timestamp    = {Sat, 17 Jul 2021 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/phd/dnb/Mayer20a.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/isbi/BohmMB20,
  author       = {Anton B{\"{o}}hm and
                  Nikolaus Mayer and
                  Thomas Brox},
  title        = {Diskmask: Focusing Object Features for Accurate Instance Segmentation
                  of Elongated or Overlapping Objects},
  booktitle    = {17th {IEEE} International Symposium on Biomedical Imaging, {ISBI}
                  2020, Iowa City, IA, USA, April 3-7, 2020},
  pages        = {230--234},
  publisher    = {{IEEE}},
  year         = {2020},
  url          = {https://doi.org/10.1109/ISBI45749.2020.9098435},
  doi          = {10.1109/ISBI45749.2020.9098435},
  timestamp    = {Wed, 04 Oct 2023 17:01:25 +0200},
  biburl       = {https://dblp.org/rec/conf/isbi/BohmMB20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/iros/KaljacaMVMHB19,
  author       = {Dejan Kaljaca and
                  Nikolaus Mayer and
                  Bastiaan A. Vroegindeweij and
                  Angelo Mencarelli and
                  Eldert J. van Henten and
                  Thomas Brox},
  title        = {Automated Boxwood Topiary Trimming with a Robotic Arm and Integrated
                  Stereo Vision\({}^{\mbox{*}}\)},
  booktitle    = {2019 {IEEE/RSJ} International Conference on Intelligent Robots and
                  Systems, {IROS} 2019, Macau, SAR, China, November 3-8, 2019},
  pages        = {5542--5549},
  publisher    = {{IEEE}},
  year         = {2019},
  url          = {https://doi.org/10.1109/IROS40897.2019.8968446},
  doi          = {10.1109/IROS40897.2019.8968446},
  timestamp    = {Sat, 05 Sep 2020 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/iros/KaljacaMVMHB19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/ijcv/MayerIFHCDB18,
  author       = {Nikolaus Mayer and
                  Eddy Ilg and
                  Philipp Fischer and
                  Caner Hazirbas and
                  Daniel Cremers and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {What Makes Good Synthetic Training Data for Learning Disparity and
                  Optical Flow Estimation?},
  journal      = {Int. J. Comput. Vis.},
  volume       = {126},
  number       = {9},
  pages        = {942--960},
  year         = {2018},
  url          = {https://doi.org/10.1007/s11263-018-1082-6},
  doi          = {10.1007/S11263-018-1082-6},
  timestamp    = {Sat, 30 Sep 2023 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/ijcv/MayerIFHCDB18.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/abs-1801-06397,
  author       = {Nikolaus Mayer and
                  Eddy Ilg and
                  Philipp Fischer and
                  Caner Hazirbas and
                  Daniel Cremers and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {What Makes Good Synthetic Training Data for Learning Disparity and
                  Optical Flow Estimation?},
  journal      = {CoRR},
  volume       = {abs/1801.06397},
  year         = {2018},
  url          = {http://arxiv.org/abs/1801.06397},
  eprinttype    = {arXiv},
  eprint       = {1801.06397},
  timestamp    = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1801-06397.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/cvpr/IlgMSKDB17,
  author       = {Eddy Ilg and
                  Nikolaus Mayer and
                  Tonmoy Saikia and
                  Margret Keuper and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks},
  booktitle    = {2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
                  {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
  pages        = {1647--1655},
  publisher    = {{IEEE} Computer Society},
  year         = {2017},
  url          = {https://doi.org/10.1109/CVPR.2017.179},
  doi          = {10.1109/CVPR.2017.179},
  timestamp    = {Fri, 24 Mar 2023 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/cvpr/IlgMSKDB17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/cvpr/UmmenhoferZUMID17,
  author       = {Benjamin Ummenhofer and
                  Huizhong Zhou and
                  Jonas Uhrig and
                  Nikolaus Mayer and
                  Eddy Ilg and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {DeMoN: Depth and Motion Network for Learning Monocular Stereo},
  booktitle    = {2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
                  {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
  pages        = {5622--5631},
  publisher    = {{IEEE} Computer Society},
  year         = {2017},
  url          = {https://doi.org/10.1109/CVPR.2017.596},
  doi          = {10.1109/CVPR.2017.596},
  timestamp    = {Fri, 24 Mar 2023 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/cvpr/UmmenhoferZUMID17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/cvpr/MayerIHFCDB16,
  author       = {Nikolaus Mayer and
                  Eddy Ilg and
                  Philip H{\"{a}}usser and
                  Philipp Fischer and
                  Daniel Cremers and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {A Large Dataset to Train Convolutional Networks for Disparity, Optical
                  Flow, and Scene Flow Estimation},
  booktitle    = {2016 {IEEE} Conference on Computer Vision and Pattern Recognition,
                  {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016},
  pages        = {4040--4048},
  publisher    = {{IEEE} Computer Society},
  year         = {2016},
  url          = {https://doi.org/10.1109/CVPR.2016.438},
  doi          = {10.1109/CVPR.2016.438},
  timestamp    = {Sat, 30 Sep 2023 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/cvpr/MayerIHFCDB16.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/IlgMSKDB16,
  author       = {Eddy Ilg and
                  Nikolaus Mayer and
                  Tonmoy Saikia and
                  Margret Keuper and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks},
  journal      = {CoRR},
  volume       = {abs/1612.01925},
  year         = {2016},
  url          = {http://arxiv.org/abs/1612.01925},
  eprinttype    = {arXiv},
  eprint       = {1612.01925},
  timestamp    = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/IlgMSKDB16.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/UmmenhoferZUMID16,
  author       = {Benjamin Ummenhofer and
                  Huizhong Zhou and
                  Jonas Uhrig and
                  Nikolaus Mayer and
                  Eddy Ilg and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {DeMoN: Depth and Motion Network for Learning Monocular Stereo},
  journal      = {CoRR},
  volume       = {abs/1612.02401},
  year         = {2016},
  url          = {http://arxiv.org/abs/1612.02401},
  eprinttype    = {arXiv},
  eprint       = {1612.02401},
  timestamp    = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/UmmenhoferZUMID16.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/MayerIHFCDB15,
  author       = {Nikolaus Mayer and
                  Eddy Ilg and
                  Philip H{\"{a}}usser and
                  Philipp Fischer and
                  Daniel Cremers and
                  Alexey Dosovitskiy and
                  Thomas Brox},
  title        = {A Large Dataset to Train Convolutional Networks for Disparity, Optical
                  Flow, and Scene Flow Estimation},
  journal      = {CoRR},
  volume       = {abs/1512.02134},
  year         = {2015},
  url          = {http://arxiv.org/abs/1512.02134},
  eprinttype    = {arXiv},
  eprint       = {1512.02134},
  timestamp    = {Mon, 13 Aug 2018 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/MayerIHFCDB15.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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