LSD-SLAM: Large-scale direct monocular SLAM J Engel, T Schöps, D Cremers European conference on computer vision, 834-849, 2014 | 4656 | 2014 |
Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE International Conference on Computer Vision, 2758-2766, 2015 | 4345 | 2015 |
Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE International Conference on Computer Vision, 2758-2766, 2015 | 4345 | 2015 |
A benchmark for the evaluation of RGB-D SLAM systems J Sturm, N Engelhard, F Endres, W Burgard, D Cremers 2012 IEEE/RSJ international conference on intelligent robots and systems …, 2012 | 3922 | 2012 |
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2945 | 2016 |
Direct sparse odometry J Engel, V Koltun, D Cremers IEEE transactions on pattern analysis and machine intelligence 40 (3), 611-625, 2017 | 2943 | 2017 |
A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape D Cremers, M Rousson, R Deriche International journal of computer vision 72, 195-215, 2007 | 1388 | 2007 |
Dense visual SLAM for RGB-D cameras C Kerl, J Sturm, D Cremers 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 1122 | 2013 |
3-D mapping with an RGB-D camera F Endres, J Hess, J Sturm, D Cremers, W Burgard IEEE transactions on robotics 30 (1), 177-187, 2013 | 1092 | 2013 |
One-shot video object segmentation S Caelles, KK Maninis, J Pont-Tuset, L Leal-Taixé, D Cremers, ... Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1078 | 2017 |
An evaluation of the RGB-D SLAM system F Endres, J Hess, N Engelhard, J Sturm, D Cremers, W Burgard 2012 IEEE international conference on robotics and automation, 1691-1696, 2012 | 1029 | 2012 |
The wave kernel signature: A quantum mechanical approach to shape analysis M Aubry, U Schlickewei, D Cremers 2011 IEEE international conference on computer vision workshops (ICCV …, 2011 | 923 | 2011 |
Variational methods in imaging O Scherzer, M Grasmair, H Grossauer, M Haltmeier, F Lenzen Springer Science+ Business Media LLC, 2009 | 887 | 2009 |
Fusenet: Incorporating depth into semantic segmentation via fusion-based cnn architecture C Hazirbas, L Ma, C Domokos, D Cremers Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 848 | 2017 |
Semi-dense visual odometry for a monocular camera J Engel, J Sturm, D Cremers Proceedings of the IEEE international conference on computer vision, 1449-1456, 2013 | 768 | 2013 |
Robust odometry estimation for RGB-D cameras C Kerl, J Sturm, D Cremers 2013 IEEE international conference on robotics and automation, 3748-3754, 2013 | 755 | 2013 |
Large-scale direct SLAM with stereo cameras J Engel, J Stückler, D Cremers 2015 IEEE/RSJ international conference on intelligent robots and systems …, 2015 | 726 | 2015 |
Flownet: Learning optical flow with convolutional networks P Fischer, A Dosovitskiy, E Ilg, P Häusser, C Hazırbaş, V Golkov, ... arXiv preprint arXiv:1504.06852, 2015 | 717 | 2015 |
Mot20: A benchmark for multi object tracking in crowded scenes P Dendorfer, H Rezatofighi, A Milan, J Shi, D Cremers, I Reid, S Roth, ... arXiv preprint arXiv:2003.09003, 2020 | 692 | 2020 |
An introduction to total variation for image analysis A Chambolle, V Caselles, D Cremers, M Novaga, T Pock Theoretical foundations and numerical methods for sparse recovery 9 (263-340 …, 2010 | 633 | 2010 |