FedericoTombari

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Federico Tombari

Contact

Federico Tombari, Ph.D

  • Email: tombari|[at]|in.tum.de

  • Address:

Chair for Computer Aided Medical Procedures & Augmented Reality
Fakultät für Informatik
Technische Universität München
Boltzmannstr. 3
85748 Garching b. München

At the CAMP Chair?, I am currently leading the computer vision team, and I coordinate most of the computer vision-related research activities within Prof. Navab's group.

I am particularly active in the area of 3D/RGB-D perception and applications of deep learning to computer vision.

The fields of application of my research are mostly in robotics, medical, augmented reality and autonomous driving.

News

  • Jun 2017: I will be giving an invited talk at the Machine Intelligence in Autonomous Vehicles Summit, organized in Amsterdam on June 28-29.
  • Jun 2017: We are organizing a Meetup event on Machine Perception and Augmented Reality to be held in the cool venue of Google Munich. The talk is scheduled for June 29 at 7pm and to participate you need to register online. Find all information here.
  • Apr 2017: I am giving a talk at Nvidia GTC in San Jose, California on deep learning for scene understanding. The talk is scheduled for May 8 at 11.30am in Room 210B.
  • Mar 2017: Two papers accepted at CVPR '17, one on monocular SLAM with deep learning, the other one on RGB-D object tracking. More info soon to come.
  • Feb 2017: I am an organizer of the "Deep Learning in Industry", a 3-day event held at TUM on April 3-5, 2017 and aimed at companies and start-ups interested in getting kickstarted on deep learning. More information available here.

Open Positions

  • Jun 2017: we offer an open positions for a Master Thesis with BMW on the topic of autonomous driving, supported by a stipend. We are looking for students with experience in computer vision and machine learning. Please get in touch with me if interested, sending your CV and grade transcript.
  • Mar 2017: we offer a Ph.D position supported by Toyota on a project focused on 3D perception for robotics. The ideal candidate has a strong background in programming (in particular, C++) and knowledge in computer vision and deep learning. Please get in touch with me if interested, sending your CV and grade transcript.
  • Jan 2017: we are offering a position as a Research Engineer for one year (renewable for another year), to assist our team with engineering and software development on the topic of 3D computer vision. The ideal candidate has a strong background in programming (in particular, C++) and knowledge in computer vision. Please get in touch with me if interested, sending your CV and grade transcript.

Ongoing Projects

My research activity is sponsored by industrial partners through research projects in computer vision and machine learning, for which I act as the Principal Investigator and academical supervisor. Currently active projects include:

  • Toyota, on 3D object recognition and pose estimation for service robotics
  • Google, on development of 3D perception algorithms for the Tango project
  • BMW, on the development of computer vision and deep learning technology for autonomous driving
  • Canon, on the development of algorithms for semantic mapping and incremental scene understanding from consumer depth cameras
  • IABG, on the development of 3D mapping algorithms for UAVs
  • Zeiss, on the development of computer vision technology for retinal microsurgery interventions

Teaching

Student Projects

Available
DA/MA/BAPerception for humanoid and agricultural robotics
(Federico Tombari Daniel Wahrmann, Prof. Nassir Navab)
DA/MA/BACamera based Head-Up-Display Brightness Control
(Nikolas Brasch, Federico Tombari, Prof. Nassir Navab)

Running
DA/MA/BAAction Recognition and Generation With RNNs
(Huseyin Coskun, Christian Rupprecht, Federico Tombari, Prof. Nassir Navab)
Master ThesisVision-based Robotic Pick and Place (with KUKA Roboter GmbH)
(DavidTan, Salvatore Virga, Federico Tombari, Prof. Nassir Navab)
DA/MA/BAInvariant Landmark Detection for highly accurate positioning
(Jakob Mayr, Federico Tombari, Prof. Nassir Navab)
DA/MA/BAAdversarial Multiple Hypothesis Prediction
(Christian Rupprecht, Iro Laina, Federico Tombari, Prof. Nassir Navab)
IDPMedical Augmented Reality with SLAM-based perception
(Federico Tombari, Ulrich Eck, Prof. Nassir Navab)
Master ThesisDeep Intrinsic Image Decomposition
(Christian Rupprecht, Iro Laina, Federico Tombari, Prof. Nassir Navab)
Master ThesisRGB-D Object Detection with Deep Learning
(Wadim Kehl, Federico Tombari, Prof. Nassir Navab)
Master ThesisEfficient Object Detection using Fully Convolutional Neural Networks
(Iro Laina, Federico Tombari, Prof. Nassir Navab)

List of Publications at CAMP

2017
W. Kehl, F. Tombari, S. Ilic, N. Navab
Real-Time 3D Model Tracking in Color and Depth on a Single CPU Core
Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, July 2017 (bib)
C. Rupprecht, I. Laina, R. DiPietro, M. Baust, F. Tombari, N. Navab, G. D. Hager
Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses
International Conference on Computer Vision (ICCV 2017), Venice, Italy, October 2017 (bib)
W. Kehl, F. Manhardt, F. Tombari, S. Ilic, N. Navab
SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again
Intenational Conference on Computer Vision (ICCV), Venice, Italy, October 2017 (bib)
I. Laina, N. Rieke, C. Rupprecht, J. Page Vizcaino, A. Eslami, F. Tombari, N. Navab
Concurrent Segmentation and Localization for Tracking of Surgical Instruments
Accepted to Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec, Canada, September 2017.
A pre-print version is available online at arXiv.
The first two authors contribute equally to this paper.
(bib)
K. Tateno , F. Tombari, I. Laina, N. Navab
CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, June, 2017.
The first two authors contribute equally to this paper.
(bib)
K. Tateno , F. Tombari, N. Navab
Large Scale and Long Standing Simultaneous Reconstruction and Segmentation
Computer Vision and Image Understanding (CVIU), Volume 157, Pages 138-150, April, 2017.
The final publication is available at http://www.sciencedirect.com/science/article/pii/S1077314216300662
(bib)
J. Page Vizcaino, N. Rieke, D. J. Tan , F. Tombari, A. Eslami, N. Navab
Automatic Initialization and Failure Detection for Surgical Tool Tracking in Retinal Microsurgery
Workshops Bildverarbeitung fuer die Medizin (BVM), Heidelberg, March 12-14, 2017. (bib)
D. J. Tan , F. Tombari, N. Navab
Real-Time Accurate 3D Head Tracking and Pose Estimation with Consumer RGB-D Cameras
International Journal of Computer Vision (bib)
2016
W. Kehl, T. Holl, F. Tombari, S. Ilic, N. Navab
An Octree-Based Approach towards Efficient Variational Range Data Fusion
British Machine Vision Conference (BMVC), York, UK, September 2016 (bib)
W. Kehl, F. Milletari, F. Tombari, S. Ilic, N. Navab
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation
European Conference On Computer Vision (ECCV), Amsterdam, The Netherlands, October 2016 (bib)
I. Laina, C. Rupprecht, V. Belagiannis, F. Tombari, N. Navab
Deeper Depth Prediction with Fully Convolutional Residual Networks (Oral Presentation)
International Conference on 3DVision (3DV), Stanford University, California, USA, October 2016.
The first two authors contribute equally to this paper.
(bib)
N. Rieke, D. J. Tan , F. Tombari, J. Page Vizcaino, C. Amat di San Filippo, A. Eslami, N. Navab
Real-Time Online Adaption for Robust Instrument Tracking and Pose Estimation
Proceedings of the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016 (bib)
F. Achilles, A.E. Ichim, H. Coskun, F. Tombari, S. Noachtar, N. Navab
PatientMocap: Human Pose Estimation under Blanket Occlusion for Hospital Monitoring Applications
Proceedings of the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016 (bib)
C. Li , H. Xiao, K. Tateno , F. Tombari, N. Navab, G. D. Hager
Incremental Scene Understanding on Dense SLAM
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October, 2016. (bib)
C. Rupprecht, C. Lea, F. Tombari, N. Navab, G. D. Hager
Sensor Substitution for Video-based Action Recognition
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), Daejeon, Korea, October 2016 (bib)
N. Rieke, D. J. Tan , C. Amat di San Filippo, F. Tombari, M. Alsheakhali, V. Belagiannis, A. Eslami, N. Navab
Real-time Localization of Articulated Surgical Instruments in Retinal Microsurgery
Medical Image Analysis, vol. 34, 82-100, 2016. The original publication is available online at medicalimageanalysisjournal.com. A free version is available until November 17,2016 (bib)
F. Achilles, F. Tombari, V. Belagiannis, A.M. Loesch, S. Noachtar, N. Navab
Convolutional neural networks for real-time epileptic seizure detection
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Taylor & Francis, 2016 (bib)
F. Grün, C. Rupprecht, N. Navab, F. Tombari
A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks
International Conference on Machine Learning (ICML) Workshop on Visualization for Deep Learning, New York, USA, June 23rd, 2016 (bib)
K. Tateno , F. Tombari, N. Navab
When 2.5D is not enough: Simultaneous Reconstruction, Segmentation and Recognition on dense SLAM
IEEE International Conference on Robotics and Automation (ICRA), Stockholm, May 2016 (bib)
2015
W. Kehl, F. Tombari, N. Navab, S. Ilic, V. Lepetit
Hashmod: A Hashing Method for Scalable 3D Object Detection
British Machine Vision Conference (BMVC), Swansea, UK, September 2015 (bib)
K. Tateno , F. Tombari, N. Navab
Real-Time and Scalable Incremental Segmentation on Dense SLAM
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015 (bib)
D. J. Tan , F. Tombari, S. Ilic, N. Navab
A Versatile Learning-based 3D Temporal Tracker: Scalable, Robust, Online
International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015 (bib)
C.-H. Huang, F. Tombari, N. Navab
Repeatable Local Coordinate Frames for 3D Human Motion Tracking: from Rigid to Non-Rigid
International Conference on 3D Vision (3DV), Lyon, France, Oct. 20, 2015 (bib)
D. J. Tan , F. Tombari, N. Navab
A Combined Generalized and Subject-Specific 3D Head Pose Estimation
International Conference on 3D Vision (3DV), Lyon, France, October 2015 (bib)
V. Zografos, A. Valentinitsch, M. Rempfler, F. Tombari, B. Menze
Hierarchical multi-organ segmentation without registration in 3D abdominal CT images
MICCAI-MCV 2015, 2015, Munich, Germany (bib)
N. Rieke, D. J. Tan , M. Alsheakhali, F. Tombari, C. Amat di San Filippo, V. Belagiannis, A. Eslami, N. Navab
Surgical Tool Tracking and Pose Estimation in Retinal Microsurgery
Proceedings of the 18th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Munich, Germany, October 2015 (bib)
F. Milletari, A. Ahmadi, C. Kroll, C. Hennersperger, F. Tombari, A. Shah, A. Plate, K. Bötzel, N. Navab
Robust Segmentation of Various Anatomies in 3D Ultrasound Using Hough Forests and Learned Data Representations
MICCAI 2015, the 18th International Conference on Medical Image Computing and Computer Assisted Intervention (bib)
S. Habert, Ma Meng, W. Kehl, Xiang Wang, F. Tombari, P. Fallavollita, N. Navab
Augmenting mobile C-arm fluoroscopes via Stereo-RGBD sensors for multimodal visualization
International Symposium on Mixed and Augmented Reality (ISMAR), 2015 (bib)
F. Milletari, W. Kehl, F. Tombari, S. Ilic, A. Ahmadi, N. Navab
Universal Hough dictionaries for object tracking
British Machine Vision Conference (BMVC), Swansea, UK, September 2015 (bib)

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Title: Dr.
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Firstname: Federico
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Lastname: Tombari
Picture: FedericoTombari.png
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Nationality: Cosmopolitan
Languages: English
Groups: Computer Vision, Industrial Augmented Reality
Expertise: Computer Vision, Industrial Augmented Reality
Position: Scientific Staff
Status: Active
Emailbefore: tombari
Emailafter: in.tum.de
Room: 03.13.040
Telephone: +49 089-289 17082
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