FabianManhardt

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

Fabian Manhardt

Contact

Fabian Manhardt

Fabian Manhardt ORCID iD icon

  • Email: fabian.manhardt[at]tum.de

  • Position: PhD Candidate

  • Address:

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

News

  • Jul 3 (2018): 2 Papers accepted to ECCV '18 (1 first author as oral).
  • Aug 5 (2017): Our SSD6D paper at ICCV '17 in Venice just got selected as Oral presentation

Research Topics

I am currently involved in conducting research in the following research areas.

  • Computer Vision.
  • Deep Learning.

Student Projects

If you are interested in projects in the area of Computer Vision and Deep Learning, you are always welcome to drop by my office.

Available

Running
DA/MA/BAEdward Cornelius KrubasikClass-Level Object Detection and Pose Estimation from a Single RGB Image Only
(Fabian Manhardt, Federico Tombari, Prof. Nassir Navab)
Finished
DA/MA/BADiego Martin ArroyoDealing with the ambiguity induced by object symmetry in pose estimation tasks
(Fabian Manhardt, Federico Tombari, Prof. Nassir Navab)

Teaching Assistance

Active research projects

Rigid 3D Object Detection

Rigid 3D Object Detection

Object detection and localization is a crucial step for inspection and manipulation tasks in robotic and industrial applications. We present an object detection and localization scheme for 3D objects that combines intensity and depth data. A novel multimodal, scale- and rotation-invariant feature is used to simultaneously describe the object's silhouette and surface appearance. The object's position is determined by matching scene and model features via a Hough-like local voting scheme. The proposed method is quantitatively and qualitatively evaluated on a large number of real sequences, proving that it is generic and highly robust to occlusions and clutter. Comparisons with state of the art methods demonstrate comparable results and higher robustness with respect to occlusions.

SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again

ssd6d_out.jpg ssd6d_coffee.jpg

Deep Model-Based 6D Pose Refinement in RGB

Code can be found here. Trained models can be downloaded here.

List of Publications

2018
F. Manhardt, W. Kehl, N. Navab, F. Tombari
Deep Model-Based 6D Pose Refinement in RGB
European Conference On Computer Vision (ECCV), Munich, Germany, September 2018 [oral].
The first two authors contributed equally to this paper.
(bib)
T. Hodan, F. Michel, E. Brachmann, W. Kehl, A. Buch, D. Kraft, B. Drost, J. Vidal, S. Ihrke, X. Zabulis, C. Sahin, F. Manhardt, F. Tombari, T.K. Kim, J. Matas, C. Rother
BOP: Benchmark for 6D Object Pose Estimation
European Conference On Computer Vision (ECCV), Munich, Germany, September 2018. (bib)
2017
W. Kehl, F. Manhardt, F. Tombari, S. Ilic, N. Navab
SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again
International Conference on Computer Vision (ICCV), Venice, Italy, October 2017 [oral].
The first two authors contributed equally to this paper.
(bib)
2015
A. Luckow, K. Kennedy, F. Manhardt, E. Djerekarov, A. Apon
Automotive big data: Applications, workloads and infrastructures
International Conference on Big Data (Big Data), Santa Clara, CA, USA, December 2015 (bib)


UsersForm
Title: M.Sc.
Circumference of your head (in cm):  
Firstname: Fabian
Middlename:  
Lastname: Manhardt
Picture: IMG_1130.jpg
Birthday: 20.10.1992
Nationality: Bavaria
Languages: English, German
Groups: Computer Vision
Expertise: Computer Vision
Position: Scientific Staff
Status: Active
Emailbefore: fabian.manhardt
Emailafter: tum.de
Room: 3.13.040
Telephone: +49 (89) 289 - 19417
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Edit | Attach | Refresh | Diffs | More | Revision r1.34 - 11 Aug 2018 - 15:08 - FabianManhardt

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