Doctoral School Projects
Master Thesis or Doctoral School Projects
- Improving Object Detection and Tracking with Scene Prior
- Study on the Impact of Anonymization on Training Data
- Object association using Monte Carlo Tree Search
- GPT Enhanced Physical-based Dataset Generation for Computer Vision Task
- Unveiling History: Matching Visual Archives with Newspaper Events
- Translate GPT into native Fribourg Patois
- Multi-Video Feed Analysis Using Applied Deep Learning: Enhancing Recycling Efficiency through Comparative Object Detection and Classification at Sorting Machine Stations (CVLab x Wasteflow)
- 3D Medical Image Analysis beyond Voxels
- STReAKS: Synthetic sTreak Rendering for sAtellite Kinematics and Surveillance
- Waste Detection in real-time: Object detection of waste type from the fall of waste in a waste cell (CVLab x Wasteflow)
- Object detection and classification of waste type and mass assessment as it moves along a conveyor belt (CVLab x Wasteflow)
- Applied Deep Learning for Computer Aided Engineering
- Spacecraft Dataset Development for Unseen and Occluded Targets
- Quantized Neural Networks for Space Applications
- Deep Learning for Nuclear Fusion
- Promoting Connectivity of Linear Structures in 3D Microscopy Images
- Modeling People and their Clothes in Crowded Scenes
- Multi-task Active Learning
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
This project aims to advance the field of object tracking by employing sophisticated decision algorithms like Monte Carlo Tree Search (MCTS) and its reinforcement learning variant, AlphaZero, to enhance the association of people detection across different frames or views.
In particular we are targeting the task of 3D tracking and long-term tracking of people. The first step toward that goal will be to build a multi-camera dataset suitable for those tasks. Initially the student will design a multi-view annotation tools that will leverage camera calibration to minimize annotation cost.
This project is dedicated to understanding how different anonymization techniques, particularly face blurring, affect the performance of detection models. By systematically blurring faces in training datasets and evaluating the resulting model accuracies, we aim to identify anonymization strategies that preserve the utility of the data while ensuring privacy.Project GoalsThe primary objectives of this project are:To (…)
Develop a comprehensive framework for generating near-photorealistic images that accurately represent deformable objects and changing materials.
The project presented here aims to address these limitations by fine-tuning a Large Language Model (LLM) to the specific cultural and linguistic characteristics of the Canton de Fribourg.
Through this project, you will be developing a solution for a real-world application that will be used in the future within WasteFlow service and will help optimize recycling.
Through this project, you will be developing a solution for real-world application that will be used in the future within WasteFlow service and will help optimize recycling.
Five instances of Liver extracted from MRI data. The black dot indicates a pseudo key point.In this project, we plan to explore methods to match/align shapes extracted from biomedical images, based on shape and texture-based features. By doing so, we will be able to analyze the variations of these structures over time and compare them (…)
The goal of this project is to develop a tool that allows the insertion of realistic synthetic observations of space objects into astronomical images.
DescriptionDifferent visual tasks are often strongly and obviously correlated. For instance, having surface normals simplifies estimating the depth of an image, knowing segmentation could help detect objects, etc. Our intuition implies the existence of a special structure among visual tasks. Extracting this structure would allow us to seamlessly reuse supervision among related tasks or solve (…)
Deep learning based approaches can be used for a wide range of space applications such as on-board data processing for observation satellite and collision prevention, spacecraft rendezvous, etc. Unfortunately, the deep learning models are very computational intensive and require huge amount of resources and power consumption. In recent years, some techniques like quantization, pruning and (…)
Computer Aided Engineering (CAE) is at the core of modern industrial engineering and manufacturing. However, the current CAE applications suffer from significant time and human resource expenses. Our goal is to leverage deep learning techniques to automate the CAE process and reduce the R&D costs for the industry.