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spezial:bib [2018/07/13 17:23] Dr. Vladimir Golkov old revision restored (2018/07/13 17:19) |
spezial:bib [2019/02/21 16:04] Rui Wang |
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@STRING{ismar= {International Symposium on Mixed and Augmented Reality}} | @STRING{ismar= {International Symposium on Mixed and Augmented Reality}} | ||
- | on | + | |
@STRING{ai = {Artificial Intelligence}} | @STRING{ai = {Artificial Intelligence}} | ||
Line 7034: | Line 7034: | ||
booktitle = iros, | booktitle = iros, | ||
month = sept, | month = sept, | ||
- | year = {2015}, | + | year = {2015} |
- | note = {to appear} | + | |
} | } | ||
Line 7502: | 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 7618: | Line 7617: | ||
@article{Mecca2016Single, | @article{Mecca2016Single, | ||
- | author={Mecca, | + | author={Mecca, |
title={{A Single-Lobe Photometric Stereo Approach for Heterogeneous Material}}, | title={{A Single-Lobe Photometric Stereo Approach for Heterogeneous Material}}, | ||
journal={SIAM Journal on Imaging Sciences}, | journal={SIAM Journal on Imaging Sciences}, | ||
Line 7767: | Line 7766: | ||
@inproceedings{QueauCVPR2017, | @inproceedings{QueauCVPR2017, | ||
address = {Honlulu, USA}, | address = {Honlulu, USA}, | ||
- | author = {Queau, Y. and Wu, T. and Lauze, F. and Durou, J.-D. and Cremers, D.}, | + | author = {Quéau, Y. and Wu, T. and Lauze, F. and Durou, J.-D. and Cremers, D.}, |
booktitle = cvpr, | booktitle = cvpr, | ||
title = {{A Non-Convex Variational Approach to Photometric Stereo under Inaccurate Lighting}}, | title = {{A Non-Convex Variational Approach to Photometric Stereo under Inaccurate Lighting}}, | ||
Line 7784: | Line 7783: | ||
year = " | year = " | ||
| | ||
- | note = {{<a href=" | + | note = {{<a href=" |
| | ||
} | } | ||
- | @InProceedings{hazirbas17ddff, | + | @InProceedings{hazirbas18ddff, |
- | | + | |
- | | + | |
- | | + | |
title = {{<a href=" | title = {{<a href=" | ||
- | year = "2017", | + | year = "2018", |
- | | + | month = " |
+ | | ||
note = {{<a href=" | note = {{<a href=" | ||
| | ||
Line 7954: | Line 7952: | ||
keywords={rgb-d, | keywords={rgb-d, | ||
note = {{<a href="/ | note = {{<a href="/ | ||
+ | } | ||
+ | |||
+ | |||
+ | @article{Haefner2018, | ||
+ | title = {Photometric Depth Super-Resolution}, | ||
+ | | ||
+ | | ||
+ | year = {2018}, | ||
+ | | ||
+ | note = {{<a href="/ | ||
+ | {<a href=" | ||
+ | keywords={rgb-d, | ||
+ | } | ||
+ | |||
+ | @article{rodola2018funmaprep, | ||
+ | title = {Functional Maps Representation on Product Manifolds}, | ||
+ | | ||
+ | | ||
+ | year = {2019}, | ||
+ | note = {{<a href=" | ||
+ | } | ||
+ | |||
+ | |||
+ | @inproceedings{Haefner2018CVPR, | ||
+ | title = {Fight ill-posedness with ill-posedness: | ||
+ | | ||
+ | | ||
+ | (CVPR)}, | ||
+ | year = {2018}, | ||
+ | | ||
+ | note = {{<a href="/ | ||
+ | {<a href=" | ||
+ | award = {Spotlight Presentation}, | ||
+ | keywords={rgb-d, | ||
} | } | ||
Line 7964: | Line 7996: | ||
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}, | ||
| | ||
- | note = {{<a href=" | + | note = {{<a href=" |
+ | keywords={rgb-d, | ||
} | } | ||
Line 7970: | Line 8003: | ||
@inproceedings{wang2017stereoDSO, | @inproceedings{wang2017stereoDSO, | ||
title={Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras}, | title={Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras}, | ||
- | author={Wang, R. and Schw\" | + | |
booktitle={International Conference on Computer Vision (ICCV)}, | booktitle={International Conference on Computer Vision (ICCV)}, | ||
year={2017}, | year={2017}, | ||
month={October}, | month={October}, | ||
address={Venice, | address={Venice, | ||
- | keywords={dso, | + | keywords={dso, |
- | note = {{<a href="/ | + | note = {{<a href="/ |
} | } | ||
Line 8006: | Line 8039: | ||
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 8076: | Line 8108: | ||
titleurl = {bergmann17calibration.pdf}, | titleurl = {bergmann17calibration.pdf}, | ||
keywords={visual odometry, calibration, | keywords={visual odometry, calibration, | ||
- | note = {{This paper was also selected by ICRA' | + | note = {{This paper was also selected by ICRA' |
award = {ICRA' | award = {ICRA' | ||
} | } | ||
Line 8121: | Line 8153: | ||
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{Swazinna-et-al-ismrm2019, | ||
+ | author = {P. Swazinna and V. Golkov and I. Lipp and E. Sgarlata and V. Tomassini and D. K. Jones and D. Cremers}, | ||
+ | title = {Negative-Unlabeled Learning for Diffusion MRI}, | ||
+ | year = {2019}, | ||
+ | booktitle = ismrm, | ||
+ | keywords = {deep learning, machine learning, medical imaging, magnetic resonance imaging, diffusion MRI, weakly-supervised learning, positive-unlabeled learning, semi-supervised learning, localization, | ||
} | } | ||
Line 8131: | Line 8171: | ||
} | } | ||
+ | |||
+ | @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 8142: | Line 8192: | ||
} | } | ||
- | @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 8157: | Line 8214: | ||
booktitle= ijcv, | booktitle= ijcv, | ||
year = {2018}, | year = {2018}, | ||
+ | month = {September}, | ||
eprint = {arXiv: | eprint = {arXiv: | ||
note = {{<a href=" | note = {{<a href=" | ||
keywords = {deeplearning} | keywords = {deeplearning} | ||
} | } | ||
+ | |||
@InProceedings{Frerix-et-al-18, | @InProceedings{Frerix-et-al-18, | ||
Line 8169: | Line 8228: | ||
year = " | year = " | ||
note = {{<a href=" | note = {{<a href=" | ||
- | } | ||
- | |||
- | @inproceedings{Haefner2018CVPR, | ||
- | title = {Fight ill-posedness with ill-posedness: | ||
- | | ||
- | | ||
- | (CVPR)}, | ||
- | year = {2018}, | ||
- | | ||
- | note = {{<a href="/ | ||
- | {<a href=" | ||
- | award = {Spotlight Presentation}, | ||
} | } | ||
Line 8229: | Line 8276: | ||
@InProceedings{laude-et-al-transductive, | @InProceedings{laude-et-al-transductive, | ||
- | author = "E. Laude and J.-H. Lange and J. Schüpfer | + | author = "E. Laude and J.-H. Lange and J. Sch{\" |
- | title = " | + | title = " |
booktitle=cvpr, | booktitle=cvpr, | ||
year = " | year = " | ||
Line 8239: | Line 8286: | ||
title = " | title = " | ||
booktitle=icra, | booktitle=icra, | ||
- | year=" | + | year=" |
- | note= to appear | + | |
} | } | ||
@InProceedings{stumberg18vidso, | @InProceedings{stumberg18vidso, | ||
Line 8248: | Line 8294: | ||
year = " | year = " | ||
month = " | month = " | ||
- | note = {{to appear, }{<a href="/ | + | note = {{<a href="/ |
keywords={dso, | keywords={dso, | ||
} | } | ||
Line 8259: | Line 8305: | ||
year = " | year = " | ||
month = " | month = " | ||
- | note = {accepted, to appear, | + | note = {{<a href=" |
keywords = tumvi | keywords = tumvi | ||
} | } | ||
Line 8269: | Line 8315: | ||
title = "LDSO: Direct Sparse Odometry with Loop Closure", | title = "LDSO: Direct Sparse Odometry with Loop Closure", | ||
booktitle = iros, | booktitle = iros, | ||
- | % | + | |
year = " | year = " | ||
month = " | month = " | ||
- | note = {accepted, to appear}, | + | note = {{<a href=" |
- | keywords = dso | + | keywords = {dso, ldso} |
} | } | ||
Line 8301: | Line 8347: | ||
booktitle = {Robotics and Automation Letters}, | booktitle = {Robotics and Automation Letters}, | ||
publisher = {IEEE}, | publisher = {IEEE}, | ||
- | | + | |
- | | + | |
} | } | ||
Line 8322: | Line 8368: | ||
month = " | month = " | ||
award = {Oral Presentation}, | award = {Oral Presentation}, | ||
+ | note = {{<a href=" | ||
} | } | ||
Line 8331: | Line 8378: | ||
month = " | month = " | ||
award = {Oral Presentation}, | award = {Oral Presentation}, | ||
- | note = {{<a href=" | + | note = {{<a href=" |
+ | keywords = {dso, dvso, deep learning, deeplearning, | ||
} | } | ||
@InProceedings{schubert2018drso, | @InProceedings{schubert2018drso, | ||
- | author = "D. Schubert | + | author = "D. Schubert and N. Demmel |
title = " | title = " | ||
booktitle = eccv, | booktitle = eccv, | ||
Line 8341: | Line 8389: | ||
month = " | month = " | ||
award = {Oral Presentation}, | 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.}, | ||
+ | award = {Best Cognitive Robotics Paper Finalist}, | ||
+ | } | ||
+ | @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=" | ||
+ | } | ||
+ | |||
+ | @InProceedings{estellers2018, | ||
+ | author = "V. Estellers and F. Schmidt and D. Cremers", | ||
+ | title = " | ||
+ | booktitle = {Proc. of the Int. Conference on 3D Vision (3DV)}, | ||
+ | year = " | ||
+ | month = " | ||
+ | keywords = " | ||
+ | topic = "Shape Analysis", | ||
+ | award = {Received the Best Paper Award at 3DV 2018}, | ||
+ | note = {{<a href=" | ||
+ | |||
+ | } | ||
+ | |||
+ | @InProceedings{brucker18pose, | ||
+ | author = {M. Brucker and M. Durner and Z.-C. Márton and F. Bálint-Benczédi and M. Sundermeyer and R. Triebel}, | ||
+ | title = {{6DoF} Pose Estimation for Industrial Manipulation based on Synthetic Data}, | ||
+ | booktitle = {International Symposium on Experimental Robotics (ISER) }, | ||
+ | address = {Buenos Aires, Argentina}, | ||
+ | year = 2018, | ||
+ | month = {Nov.} | ||
+ | } | ||
+ | @InProceedings{nissler18simultaneous, | ||
+ | author = {C. Nissler and M. Durner and Z.-C. Márton and R. Triebel}, | ||
+ | title = {Simultaneous Calibration and Mapping}, | ||
+ | booktitle = {International Symposium on Experimental Robotics (ISER) }, | ||
+ | address = {Buenos Aires, Argentina}, | ||
+ | year = 2018, | ||
+ | month = {Nov.} | ||
+ | } | ||
+ | |||
+ | @article{tjaden2018region, | ||
+ | title={A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking}, | ||
+ | author={Tjaden, | ||
+ | journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, | ||
+ | year={2018}, | ||
+ | titleurl = {tjaden_et_al_pami18.pdf} | ||
+ | } | ||
+ | |||
+ | @inproceedings{wenzel18corl, | ||
+ | author = {P. Wenzel and Q. Khan and D. Cremers and L. Leal-Taixé}, | ||
+ | booktitle = {Conference on Robot Learning (CoRL)}, | ||
+ | title = {{Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs}}, | ||
+ | year = {2018}, | ||
+ | note = {{<a href=" | ||
+ | } | ||
+ | |||
+ | @article{Frerix2019, | ||
+ | author = " | ||
+ | title = " | ||
+ | journal = " | ||
+ | primaryClass = " | ||
+ | year = " | ||
+ | note = {{<a href=" | ||
+ | } |