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spezial:bib [2019/07/29 09:23] wenzel |
spezial:bib [2019/09/29 21:16] haefner |
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| 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 7967: | Line 7958: | ||
| year = {2019}, | year = {2019}, | ||
| note = {(Presented at Symposium on Geometry Processing (SGP)) {<a href=" | note = {(Presented at Symposium on Geometry Processing (SGP)) {<a href=" | ||
| + | } | ||
| + | |||
| + | @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}, | ||
| + | award = {}, | ||
| + | titleurl = {sang2020wacv.pdf}, | ||
| + | } | ||
| + | |||
| + | @article{brahimi2019springer, | ||
| + | title = {On well-posedness of uncalibrated photometric stereo under general lighting}, | ||
| + | | ||
| + | | ||
| + | year = {2019}, | ||
| + | eprint = {}, | ||
| + | eprinttype = {}, | ||
| + | eprintclass = {}, | ||
| + | titleurl = {}, | ||
| + | note = {}, | ||
| + | keywords={}, | ||
| + | } | ||
| + | |||
| + | @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="/ | ||
| + | }, | ||
| } | } | ||
| Line 8014: | Line 8043: | ||
| note = { | note = { | ||
| {<a href="/ | {<a href="/ | ||
| + | {<a href="/ | ||
| {<a href=" | {<a href=" | ||
| {<a href=" | {<a href=" | ||
| Line 8201: | Line 8231: | ||
| 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 8371: | Line 8412: | ||
| 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 8457: | Line 8488: | ||
| } | } | ||
| - | @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 8466: | Line 8497: | ||
| } | } | ||
| - | @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 8475: | Line 8506: | ||
| 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 8599: | Line 8630: | ||
| award = {Oral Presentation}, | award = {Oral Presentation}, | ||
| note = {{<a href=" | note = {{<a href=" | ||
| - | } | ||
| - | |||
| - | @article{moeller-et-al-19, | ||
| - | author = "M. Moeller and T. M{\" | ||
| - | title = " | ||
| - | journal = {preprint}, | ||
| - | year = " | ||
| - | note = {{<a href=" | ||
| } | } | ||
| Line 8639: | Line 8662: | ||
| journal = {preprint}, | journal = {preprint}, | ||
| year = " | year = " | ||
| - | note = {{<a href=" | + | note = {{<a href=" |
| - | keywords = {stereo, 3D reconstruction, | + | keywords = {stereo, 3D reconstruction, |
| } | } | ||
| Line 8660: | Line 8683: | ||
| year = " | year = " | ||
| note = {{<a href=" | note = {{<a href=" | ||
| - | award = {Full Oral Presentation} | + | award = {Full Oral Presentation}, |
| + | month={6} | ||
| } | } | ||
| Line 8673: | Line 8697: | ||
| @article{gn-net-19, | @article{gn-net-19, | ||
| 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 = {preprint}, | ||
| year = " | year = " | ||
| - | note = {{<a href=" | + | note = {{<a href=" |
| keywords = {gn-net} | keywords = {gn-net} | ||
| } | } | ||
| Line 8688: | Line 8712: | ||
| } | } | ||
| - | @article{control-across-weathers-19, | + | @inproceedings{control-across-weathers-19, |
| author = "Q. Khan and P. Wenzel and D. Cremers and L. Leal-Taixe", | author = "Q. Khan and P. Wenzel and D. Cremers and L. Leal-Taixe", | ||
| title = " | title = " | ||
| - | | + | |
| 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}}, | ||
| + | year = {2019} | ||
| } | } | ||
