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BOBosch Group

Master Thesis AI-Based Keypoint Refinement for Autonomous Driving(m/w/x)

Hildesheim
Full-timeInternshipOn-site
AI/ML
Data Science

Designing unified neural network architectures for keypoint refinement in autonomous driving at a developer of advanced automotive technologies. Strong Computer Vision and Deep Learning background, with Python and PyTorch proficiency required. Self-driven research project, with dedicated mentorship for thesis completion.

Requirements

  • Master studies in Computer Science, Robotics, Mathematics, Physics or comparable
  • Strong background in Computer Vision and Deep Learning
  • Proficiency in Python and PyTorch
  • Knowledge of feature matching, multi-view geometry, or SLAM (highly desirable)
  • Ownership of research with self-driven, independent, structured approach
  • Development of creative ideas and professional technical discussion skills
  • On-site presence
  • Passion for solving geometric computer vision and AI problems
  • Very good English skills
  • Enrollment at university

Tasks

  • Research and develop deep learning methods
  • Improve keypoint matching for autonomous driving
  • Design a unified neural network architecture
  • Address correspondence refinement and outlier rejection
  • Integrate uncertainty estimation into the model
  • Investigate sub-pixel precision and texture ambiguity
  • Implement and train efficient deep learning models
  • Distill architectures for real-time capability
  • Benchmark performance against state-of-the-art matchers
  • Demonstrate improvements in Visual Odometry scenarios

Education

  • Currently in higher education

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • Python
  • PyTorch
  • SLAM
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