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spezial:bib [2018/06/14 14:44] haefner |
spezial:bib [2018/09/17 08:51] Dr. Vladimir Golkov |
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| Line 7034: | Line 7034: | ||
| booktitle = iros, | booktitle = iros, | ||
| month = sept, | month = sept, | ||
| - | year = {2015}, | + | year = {2015} |
| - | note = {to appear} | + | |
| } | } | ||
| Line 7347: | Line 7346: | ||
| topic={Shape Analysis}, | topic={Shape Analysis}, | ||
| url = {http:// | url = {http:// | ||
| + | note = {{<a href=" | ||
| } | } | ||
| Line 7376: | Line 7376: | ||
| topic={Shape Analysis}, | topic={Shape Analysis}, | ||
| url = {http:// | url = {http:// | ||
| - | keywords = {Shape Analysis, Shape Matching, SHREC, Topology} | + | keywords = {Shape Analysis, Shape Matching, SHREC, Topology}, |
| + | note = {{<a href=" | ||
| } | } | ||
| Line 7500: | Line 7501: | ||
| month = mar, | month = mar, | ||
| titleurl = {engel_et_al_pami2018.pdf}, | titleurl = {engel_et_al_pami2018.pdf}, | ||
| - | keywords={mono-ds, | + | keywords={mono-ds, |
| } | } | ||
| Line 7782: | Line 7783: | ||
| year = " | year = " | ||
| | | ||
| - | note = {{<a href=" | + | note = {{<a href=" |
| | | ||
| } | } | ||
| Line 7819: | Line 7820: | ||
| title = " | title = " | ||
| journal = "IEEE Robotics and Automation Letters (RA-L)", | journal = "IEEE Robotics and Automation Letters (RA-L)", | ||
| + | volume = {3}, | ||
| + | issue = {4}, | ||
| + | pages = {2878--2885}, | ||
| year = " | year = " | ||
| - | month = "May", | + | month = "Oct", |
| + | doi = " | ||
| titleurl = {yang18challenges.pdf}, | titleurl = {yang18challenges.pdf}, | ||
| - | keywords={visual odometry, | + | keywords={Brightness; |
| - | note = {{<a href=" | + | note = {{This paper was also selected by IROS' |
| } | } | ||
| Line 7969: | Line 7974: | ||
| month={October}, | month={October}, | ||
| address={Venice, | address={Venice, | ||
| - | keywords={dso, | + | keywords={dso, |
| - | note = {{<a href="/ | + | note = {{<a href="/ |
| } | } | ||
| Line 8000: | Line 8005: | ||
| title = {How Robots Learn to Classify New Objects Trained from Small Data Sets}, | title = {How Robots Learn to Classify New Objects Trained from Small Data Sets}, | ||
| booktitle | booktitle | ||
| - | year = {2017}, | + | year = {2017} |
| - | note = {to appear} | + | |
| } | } | ||
| Line 8070: | Line 8074: | ||
| titleurl = {bergmann17calibration.pdf}, | titleurl = {bergmann17calibration.pdf}, | ||
| keywords={visual odometry, calibration, | keywords={visual odometry, calibration, | ||
| - | note = {{<a href=" | + | note = {{This paper was also selected by ICRA' |
| award = {ICRA' | award = {ICRA' | ||
| } | } | ||
| Line 8125: | Line 8129: | ||
| } | } | ||
| + | |||
| + | @inproceedings{Do-et-al-2018-pre-miRNA, | ||
| + | author = {B. T. Do and V. Golkov and G. E. G\" | ||
| + | title = {Precursor microRNA Identification Using Deep Convolutional Neural Networks}, | ||
| + | year = {2018}, | ||
| + | % howpublished = {Preprint}, | ||
| + | note = {{<a href=" | ||
| + | booktitle = {bioRxiv preprint}, | ||
| + | keywords = {precursor microRNA, pre-miRNA, miRNA, deep learning, neural networks, machine learning, deeplearning, | ||
| + | } | ||
| @inproceedings{Aljalbout-et-al-2018, | @inproceedings{Aljalbout-et-al-2018, | ||
| Line 8136: | Line 8150: | ||
| } | } | ||
| - | @InProceedings{haeusser2018associative, | + | @InProceedings{haeusser18associative, |
| author = "P. Haeusser and J. Plapp and V. Golkov and E. Aljalbout and D. Cremers", | author = "P. Haeusser and J. Plapp and V. Golkov and E. Aljalbout and D. Cremers", | ||
| title = " | title = " | ||
| - | booktitle = "under review" | + | booktitle = {Proc. of the German Conference on Pattern Recognition (GCPR)}, |
| - | year = "2018", | + | year = {2018}, |
| - | month = "November", | + | month = "October", |
| - | titleurl = {haeusser2018associative.pdf}, | + | titleurl = {haeusser18associative.pdf}, |
| keywords={Clustering, | keywords={Clustering, | ||
| } | } | ||
| + | |||
| + | |||
| + | |||
| + | |||
| + | |||
| + | |||
| + | |||
| @InProceedings{mayer18synthetic, | @InProceedings{mayer18synthetic, | ||
| Line 8173: | Line 8194: | ||
| | | ||
| note = {{<a href="/ | note = {{<a href="/ | ||
| - | {<a href=" | + | {<a href=" |
| award = {Spotlight Presentation}, | award = {Spotlight Presentation}, | ||
| } | } | ||
| Line 8233: | Line 8254: | ||
| title = " | title = " | ||
| booktitle=icra, | booktitle=icra, | ||
| - | year=" | + | year=" |
| - | note= to appear | + | |
| } | } | ||
| @InProceedings{stumberg18vidso, | @InProceedings{stumberg18vidso, | ||
| Line 8242: | Line 8262: | ||
| year = " | year = " | ||
| month = " | month = " | ||
| - | note = {{to appear, }{<a href="/ | + | note = {{<a href="/ |
| keywords={dso, | keywords={dso, | ||
| } | } | ||
| Line 8249: | Line 8269: | ||
| author = "D. Schubert and T. Goll and N. Demmel and V. Usenko and J. Stueckler and D. Cremers", | author = "D. Schubert and T. Goll and N. Demmel and V. Usenko and J. Stueckler and D. Cremers", | ||
| title = "The TUM VI Benchmark for Evaluating Visual-Inertial Odometry", | title = "The TUM VI Benchmark for Evaluating Visual-Inertial Odometry", | ||
| - | booktitle = " | + | booktitle = iros, |
| - | arXiv = " arXiv: | + | arXiv = " |
| year = " | year = " | ||
| - | month = "April", | + | month = "October", |
| - | note = {{<a href=" | + | note = {accepted, to appear, |
| keywords = tumvi | keywords = tumvi | ||
| + | } | ||
| + | |||
| + | |||
| + | |||
| + | @InProceedings{gao2018ldso, | ||
| + | author = "X. Gao and R. Wang and N. Demmel and D. Cremers", | ||
| + | title = "LDSO: Direct Sparse Odometry with Loop Closure", | ||
| + | booktitle = iros, | ||
| + | arXiv = " | ||
| + | year = " | ||
| + | month = " | ||
| + | note = {{<a href=" | ||
| + | keywords = {dso, ldso} | ||
| } | } | ||
| Line 8274: | Line 8307: | ||
| booktitle = {ArXiv preprint}, | booktitle = {ArXiv preprint}, | ||
| keywords = {deep learning, novelty detection, anomaly detection, neural networks, medical imaging, magnetic resonance imaging, diffusion MRI, deeplearning, | keywords = {deep learning, novelty detection, anomaly detection, neural networks, medical imaging, magnetic resonance imaging, diffusion MRI, deeplearning, | ||
| + | } | ||
| + | |||
| + | @article{matsuki2018_omnidso, | ||
| + | title = {Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras}, | ||
| + | author = {H. Matsuki and L. von Stumberg and V. Usenko and J. Stueckler and D. Cremers}, | ||
| + | journal = {IEEE Robotics and Automation Letters & Int. Conference on Intelligent Robots and Systems (IROS)}, | ||
| + | booktitle = {Robotics and Automation Letters}, | ||
| + | publisher = {IEEE}, | ||
| + | note = {{<a href=" | ||
| + | year = {2018} | ||
| + | } | ||
| + | |||
| + | @InProceedings{eisenberger2018divfree, | ||
| + | author = "M. Eisenberger and Z. L\" | ||
| + | title = " | ||
| + | booktitle = " | ||
| + | arXiv = " arXiv: | ||
| + | year = " | ||
| + | month = " | ||
| + | note = {{<a href=" | ||
| + | } | ||
| + | |||
| + | @InProceedings{laehner2018deepwrinkles, | ||
| + | author = "Z. L\" | ||
| + | title = " | ||
| + | booktitle | ||
| + | year = " | ||
| + | month = " | ||
| + | award = {Oral Presentation}, | ||
| + | note = {{<a href=" | ||
| + | } | ||
| + | |||
| + | @InProceedings{yang2018dvso, | ||
| + | author = "N. Yang and R. Wang and J. Stueckler and D. Cremers", | ||
| + | title = "Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry", | ||
| + | booktitle | ||
| + | year = " | ||
| + | month = " | ||
| + | award = {Oral Presentation}, | ||
| + | note = {{<a href=" | ||
| + | keywords = {dso, dvso, deep learning, deeplearning, | ||
| + | } | ||
| + | |||
| + | @InProceedings{schubert2018drso, | ||
| + | author = "D. Schubert and N. Demmel and V. Usenko and J. Stueckler and D. Cremers", | ||
| + | title = " | ||
| + | booktitle = eccv, | ||
| + | year = " | ||
| + | month = " | ||
| + | award = {Oral Presentation}, | ||
| + | note = {{<a href="/ | ||
| + | } | ||
| + | |||
| + | @InProceedings{usenko18double-sphere, | ||
| + | author = "V. Usenko and N. Demmel and D. Cremers", | ||
| + | title = "The Double Sphere Camera Model", | ||
| + | booktitle = {Proc. of the Int. Conference on 3D Vision (3DV)}, | ||
| + | year = " | ||
| + | month = " | ||
| + | eprint = {1807.08957}, | ||
| + | eprinttype = {arXiv}, | ||
| + | eprintclass = {cs.CV}, | ||
| + | note = {{<a href=" | ||
| + | keywords = double-sphere | ||
| + | } | ||
| + | |||
| + | @article{lingni18wcnn, | ||
| + | author={L. Ma, and J. Stueckler and T. Wu and D. Cremers}, | ||
| + | title={Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform}, | ||
| + | year={2018}, | ||
| + | month={Aug}, | ||
| + | booktitle = " | ||
| + | arXiv = " | ||
| + | note = {{<a href=" | ||
| + | } | ||
| + | |||
| + | @InProceedings{sundermeyer2018eccv, | ||
| + | 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}, | ||
| + | booktitle = eccv, | ||
| + | year = {2018}, | ||
| + | month = {September}, | ||
| + | award = {Best Paper Award}, | ||
| + | } | ||
| + | |||
| + | @InProceedings{denninger18iros, | ||
| + | author = {M. Denninger and R. Triebel}, | ||
| + | title = {Persistent Anytime Learning of Objects from Unseen Classes }, | ||
| + | booktitle = iros, | ||
| + | address = {Madrid, Spain}, | ||
| + | year = 2018, | ||
| + | month = {Oct.}, | ||
| + | } | ||
| + | @InProceedings{grixa18iros, | ||
| + | author = {I. Grixa and P. Schulz and W. St\" | ||
| + | title = {Appearance-Based Along-Route Localization for Planetary Missions}, | ||
| + | booktitle = iros, | ||
| + | address = {Madrid, Spain}, | ||
| + | year = 2018, | ||
| + | month = {Oct.}, | ||
| + | } | ||
| + | |||
| + | @InProceedings{chiotellis2018ilp, | ||
| + | author = {I. Chiotellis and F. Zimmermann and D. Cremers and R. Triebel}, | ||
| + | title = {Incremental Semi-Supervised Learning from Streams for Object Classification}, | ||
| + | booktitle = iros, | ||
| + | address = {Madrid, Spain}, | ||
| + | year = 2018, | ||
| + | month = {Oct.}, | ||
| + | note = {{<a href=" | ||
| } | } | ||
