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About the Role
The Computer Vision & Graphics group is seeking a student assistant to work on deep learning for scene analysis in the construction domain, focusing on synthetic data creation and transformation. The group develops AI methods for 3D model creation and scene analysis in construction by analyzing as-built data with AI and integrating it into a BIM model.
Responsibilities
- Support the development and integration of 3D pose estimation and localization methods in the building sector.
- Create synthetic reference datasets and develop Python scripts for automatic creation and annotation of training data from real building models.
- Develop scripts for processing BIM and IFC data.
- Test neural networks in the building domain.
- Create interfaces between AI modules.
Requirements
- Student in Computer Science, Electrical Engineering, or related field.
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Proficiency in Python programming.
- Familiarity with 3D data processing and computer vision concepts.
- Knowledge of BIM and IFC data formats is a plus.
- Strong analytical and problem-solving skills.
Skills
- Deep Learning
- Scene Analysis
- Synthetic Data Creation
- 3D Pose Estimation
- Localization
- Python Scripting
- BIM Data Processing
- IFC Data Processing
- Neural Network Testing
- AI Module Integration
Location
- Not specified
Work Type
- Student Assistant
Experience Level
- Student
Education Level
- Student in Computer Science, Electrical Engineering, or related field
About the Company
- The Computer Vision & Graphics group within the Vision & Imaging Technologies (VIT) department focuses on developing AI methods for 3D model creation, plan and scene analysis in the construction sector.
- They analyze as-built data (plans, images, point clouds) using artificial intelligence and integrate it into a BIM-based model.