Master Thesis or Doctoral School Projects
- 3D Pose Based Motion Correction for Physical Exercises
- Automatic typography analysis on figurative content
- Physically Constrained Deep Networks
- Iterative Human Pose Refinement via Energy Ascent
- Multi-Person Monocular 3D Pose Estimation
- Active learning of Neural Network proxies for aerodynamic optimization
- Real-time reconstruction of deformable objects
For further project offers, please contact members of the CVLAB directly.
Semester Projects (Bachelor and Master)
Most of the offered semester projects can be rephrased for a thesis and vice versa. Please contact us directly.
Administrative
Semester Projects (Bachelor and Master)
SIN and SSC students do one semester project during their Bachelor studies and one semester project during their Master studies.
Semester projects can be done in groups of two students.
Semester projects are worth 8 credits for Bachelor and 12 credits for Master.
Students must have the approval of the Professor in charge of the laboratory before registering for the given project.
Oral defense: within two weeks of the hand-in date.
Master Thesis Projects
Master Thesis Projects are started once the complete master program is finished and all the credits have been obtained.
Projects for SSC and SIN students should last 4 months at the EPFL or 6 months in the industry or in another University.
Master Thesis Projects must be done individually.
Master Thesis Projects are worth 30 credits.
Students must have the approval of the Professor in charge of the laboratory before registering for the given project.
Additional information
The proposed project aims at taking stock on the topic of automatic typographic analysis and at initiating the development of a framework to automatically extract typographic information.
Many practical continuous minimization problems, such as aerodynamic optimization, are not amenable to gradient-based optimization methods because derivatives cannot be computed directly. We recently showed that it is possible to train a Neural Network regressor as a proxy to the numerical simulator and optimize the proxy function via Gradient-Descent. [ICML 2018 Paper]. For example, we (…)
DescriptionModern CNN-based human pose estimators are constructed as regression architectures with human pose prediction as output. This formulation does not naturally involve the confidence of the estimation. Another possible solution is to regress the pose refinement directly via the CNN [2], which gives slight improvement over the ordinary regression-based techniques. However, it still suffers from (…)
With the rise of self-management for treatment of musculoskeletal disorders, people tend to exercise alone and without supervision. However it is dangerous to attempt these exercises without feedback, as it can be difficult to realize when one is performing the exercise incorrectly. This could lead to further injury. Therefore our goal is to design a (…)