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spezial:bib [2019/07/24 13:12] haefner |
spezial:bib [2019/09/23 16:19] wenzel |
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| 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}, | ||
| + | } | ||
| + | |||
| + | @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 7999: | Line 8024: | ||
| {<a href="/ | {<a href="/ | ||
| {<a href=" | {<a href=" | ||
| + | {<a href=" | ||
| }, | }, | ||
| keywords={rgb-d, | keywords={rgb-d, | ||
| Line 8004: | Line 8030: | ||
| - | @inproceedings{haefner2018, | + | @inproceedings{haefner2018cvpr, |
| title = {Fight ill-posedness with ill-posedness: | title = {Fight ill-posedness with ill-posedness: | ||
| | | ||
| Line 8013: | Line 8039: | ||
| note = { | note = { | ||
| {<a href="/ | {<a href="/ | ||
| + | {<a href="/ | ||
| {<a href=" | {<a href=" | ||
| {<a href=" | {<a href=" | ||
| Line 8200: | Line 8227: | ||
| 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 8370: | Line 8408: | ||
| 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 8456: | Line 8484: | ||
| } | } | ||
| - | @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 8465: | Line 8493: | ||
| } | } | ||
| - | @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 8474: | Line 8502: | ||
| 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 8598: | Line 8626: | ||
| 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 8638: | Line 8658: | ||
| journal = {preprint}, | journal = {preprint}, | ||
| year = " | year = " | ||
| - | note = {{<a href=" | + | note = {{<a href=" |
| - | keywords = {stereo, 3D reconstruction, | + | keywords = {stereo, 3D reconstruction, |
| } | } | ||
| Line 8659: | Line 8679: | ||
| year = " | year = " | ||
| note = {{<a href=" | note = {{<a href=" | ||
| - | award = {Full Oral Presentation} | + | award = {Full Oral Presentation}, |
| + | month={6} | ||
| } | } | ||
| Line 8672: | Line 8693: | ||
| @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 8685: | Line 8706: | ||
| year = " | year = " | ||
| note = {{<a href=" | note = {{<a href=" | ||
| + | } | ||
| + | |||
| + | @inproceedings{control-across-weathers-19, | ||
| + | author = "Q. Khan and P. Wenzel and D. Cremers and L. Leal-Taixe", | ||
| + | title = " | ||
| + | booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, | ||
| + | year = " | ||
| + | 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} | ||
| } | } | ||
