Picture of Martin Knoche

Martin Knoche, M.Sc.

Technical University of Munich

Chair of Human-Machine Communication (Prof. Rigoll)

Postal address

Postal:
Arcisstr. 21
80333 München

Research Areas

• Deep Learning
• Computer Vision
• Face Recognition single and multi camera
• Person Identification single and multi camera
• Super-Resolution single and multi camera

Publications

  • Hörmann, S.; Knoche, M.; Babaee, Ma.; Köpüklü, O.; Rigoll, G.: Outlier-Robust Neural Aggregation Network for Video Face Identification. Proc. International Conference on Image Processing (ICIP 2019), 2019, pp. 1675-1679 more… Full text ( DOI )
  • Heyn, H.-M.; Knoche, M.; Zhang, Q.; Skjetne, R.: A System for Automated Vision-Based Sea-Ice Concentration Detection and Floe-Size Distribution Indication From an Icebreaker. Proc. 36th International Conference on Ocean, Offshore and Arctic Engineering, ASME 2017, 2017, V008T07A012 more… Full text ( DOI )
  • Knoche, M.; Merget, D.; Rigoll, G.: Improving Facial Landmark Detection via a Super-Resolution Inception Network. 39th German Conference on Pattern Recognition, GCPR 2017, Springer Lecture Notes in Computer Science, 2017 more… Full text (mediaTUM)

Projects

Data-driven utilization of Multimedia Content
Partners: ProSiebenSat.1 Media SE, munich media intelligence
Period: 01.03.2018 - 30.09.2018

Facial recognition in public areas consistent with fundamental rights
Partners: Uniscon GmbH, Tüv Süd Digital Services, AXIS GmbH
Period: 01.10.2018 - 30.09.2020

Teaching

Signaltheorie (WS 2019)
Signaldarstellung Übung für Wiederholer (SS 2019)

Student projects

For inquiries regarding any student projects please apply using your most recent CV together with your grade report emphasizing your previous experience in this area and your desired starting date.

Open Topics

You can find all open topics here.

Finished Projects

2019
• Enhanced Deep Residual Networks for Single Image Super-Resolution (Scientific Seminar)
• Single Image and Multi Image Super Resolution for Face Identification (Master´s Thesis)
• Attention Mechanisms in an Appearance Matching Network (Research Internship)
• Enhanced Deep Residual Networks for Single Image Super-Resolution (Scientific Seminar)
• Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (Scientific Seminar)

2018
• Repulsion Loss - Detecting Pedestriants in a Crowd (Scientific Seminar)
• Wide Compression - Tensor Ring Nets (Scientifc Seminar)