| A joint intensity and depth co-sparse analysis model for depth map super-resolution M Kiechle, S Hawe, M Kleinsteuber Proceedings of the IEEE International Conference on Computer Vision, 1545-1552, 2013 | 125 | 2013 |
| Model-based learning of local image features for unsupervised texture segmentation M Kiechle, M Storath, A Weinmann, M Kleinsteuber IEEE Transactions on Image Processing 27 (4), 1994-2007, 2018 | 34 | 2018 |
| A bimodal co-sparse analysis model for image processing M Kiechle, T Habigt, S Hawe, M Kleinsteuber International Journal of Computer Vision 114 (2-3), 233-247, 2015 | 21 | 2015 |
| Room segmentation in 3D point clouds using anisotropic potential fields D Bobkov, M Kiechle, S Hilsenbeck, E Steinbach Multimedia and Expo (ICME), 2017 IEEE International Conference on, 727-732, 2017 | 19 | 2017 |
| Noise-resistant Unsupervised Object Segmentation in Multi-view Indoor Point Clouds. D Bobkov, S Chen, M Kiechle, S Hilsenbeck, EG Steinbach VISIGRAPP (5: VISAPP), 149-156, 2017 | 5 | 2017 |
| Photocation: tangible learning system for DSLR photography K Moser, M Kiechle, K Ryokai CHI'12 Extended Abstracts on Human Factors in Computing Systems, 1691-1696, 2012 | 2 | 2012 |
| Late fusion for person detection in camera networks M Hofmann, M Kiechle, G Rigoll Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE …, 2011 | 2 | 2011 |
| Model-based learning of co-sparse representations for image processing applications M Kiechle Technische Universität München, 2019 | | 2019 |
Martin KleinsteuberCIO & Lead Data Scientist, Mercateo AG, Munich在 tum.de 的电子邮件经过验证
