| Human skeleton tracking from depth data using geodesic distances and optical flow LA Schwarz, A Mkhitaryan, D Mateus, N Navab Image and Vision Computing 30 (3), 217-226, 2012 | 264 | 2012 |
| A deep metric for multimodal registration M Simonovsky, B Gutiérrez-Becker, D Mateus, N Navab, N Komodakis Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016 | 244 | 2016 |
| Articulated shape matching using laplacian eigenfunctions and unsupervised point registration D Mateus, R Horaud, D Knossow, F Cuzzolin, E Boyer 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008 | 242 | 2008 |
| Fast multiple organ detection and localization in whole-body MR Dixon sequences O Pauly, B Glocker, A Criminisi, D Mateus, AM Möller, S Nekolla, N Navab Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th …, 2011 | 134 | 2011 |
| Estimating human 3d pose from time-of-flight images based on geodesic distances and optical flow LA Schwarz, A Mkhitaryan, D Mateus, N Navab 2011 IEEE International Conference on Automatic Face & Gesture Recognition …, 2011 | 96 | 2011 |
| Workflow monitoring based on 3d motion features N Padoy, D Mateus, D Weinland, MO Berger, N Navab 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV …, 2009 | 88 | 2009 |
| Capsule networks against medical imaging data challenges A Jiménez-Sánchez, S Albarqouni, D Mateus Intravascular Imaging and Computer Assisted Stenting and Large-Scale …, 2018 | 86 | 2018 |
| SHREC 2010: robust correspondence benchmark A Bronstein, MM Bronstein, U Castellani, A Dubrovina, LJ Guibas, ... Eurographics Workshop on 3D Object Retrieval 10, 087-091, 2010 | 69 | 2010 |
| Inexact Matching of Large and Sparse Graphs Using Laplacian Eigenvectors. D Knossow, A Sharma, D Mateus, R Horaud GbRPR 9, 144-153, 2009 | 68 | 2009 |
| Multi-camera scene flow by tracking 3-d points and surfels F Devernay, D Mateus, M Guilbert 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 64 | 2006 |
| Manifold learning for tof-based human body tracking and activity recognition. LA Schwarz, D Mateus, V Castaneda, N Navab BMVC, 1-11, 2010 | 52 | 2010 |
| Machine learning in computer-aided diagnosis: Medical imaging intelligence and analysis: Medical imaging intelligence and analysis K Suzuki IGI Global, 2012 | 44 | 2012 |
| Endoscopic video manifolds for targeted optical biopsy S Atasoy, D Mateus, A Meining, GZ Yang, N Navab IEEE transactions on medical imaging 31 (3), 637-653, 2011 | 44 | 2011 |
| Robot visual navigation in semi-structured outdoor environments D Mateus, G Avina, M Devy Proceedings of the 2005 IEEE International Conference on Robotics and …, 2005 | 43 | 2005 |
| Recognizing multiple human activities and tracking full-body pose in unconstrained environments LA Schwarz, D Mateus, N Navab Pattern Recognition 45 (1), 11-23, 2012 | 42 | 2012 |
| SLAM combining ToF and high-resolution cameras V Castaneda, D Mateus, N Navab 2011 IEEE Workshop on Applications of Computer Vision (WACV), 672-678, 2011 | 42 | 2011 |
| Optical classification of neoplastic colorectal polyps–a computer-assisted approach (the COACH study) J Renner, H Phlipsen, B Haller, F Navarro-Avila, Y Saint-Hill-Febles, ... Scandinavian journal of gastroenterology 53 (9), 1100-1106, 2018 | 40 | 2018 |
| Stereo time-of-flight V Castaneda, D Mateus, N Navab 2011 International Conference on Computer Vision, 1684-1691, 2011 | 37 | 2011 |
| Random survival forest to predict transplant-eligible newly diagnosed multiple myeloma outcome including FDG-PET radiomics: a combined analysis of two independent prospective … B Jamet, L Morvan, C Nanni, AV Michaud, C Bailly, S Chauvie, P Moreau, ... European journal of nuclear medicine and molecular imaging 48, 1005-1015, 2021 | 33 | 2021 |
| Discriminative human full-body pose estimation from wearable inertial sensor data LA Schwarz, D Mateus, N Navab Modelling the Physiological Human: 3D Physiological Human Workshop, 3DPH …, 2009 | 32 | 2009 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenVerified email at cs.tum.edu
