Computer Vision and Geometry GroupOpen OpportunitiesFast moving objects are defined as objects that move over significant distances over exposure time of a single image or video frame. Thus, they look significantly blurred. Detection, tracking, and deblurring of such objects have been studied in recent years. However, there are still no methods for robust retrieval of such objects in large image collections. - Computer Graphics, Computer Vision, Image Processing, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition
- Master Thesis
| Extend the recent Marigold in different aspects - Computer Vision
- Master Thesis
| The goal of this project is to implement an 6DoF object pose estimation method that utilizes the embedded sensors of head-mounted devices like the Microsoft HoloLens to improve the accuracy of the 6DoF pose estimation. The proposed method will be thoroughly evaluated and compared against single-view, stereo, and multi-view baselines. - Computer Vision
- ETH Zurich (ETHZ), Master Thesis
| Tetra-NeRF [1] offers a way to represent the scene as Delaunay tetrahedralization of the input point cloud. This can be used to represent dynamic 3D scenes [2] as the deformation is performed on the vertices of the tetrahedral mesh. - Computer Vision
- Bachelor Thesis, Master Thesis
| Motivation: Explore the newly improved Habitat 3.0 simulator with a special focus on the Virtual Reality Features.
This project is meant to be an exploration task on the Habitat 3.0 simulator, exploring all the newly introduced features focusing specifically on the implementation of virtual reality tools for scene navigation. The idea is to extend these features to self created environments in Unreal Engine that build uppon Habitat - Artificial Intelligence and Signal and Image Processing
- Semester Project
| The efficacy of the diffusion model has been demonstrated across various computer vision applications, notably in image generation and editing[1][2]. This thesis aims to extend its generative capabilities to the domain of active sensing, specifically facilitating a mobile robot's autonomous exploration and mapping of its environment. Current methods for active sensing and viewpoint selection predominantly lean on either volumetric reconstruction, which necessitates manually crafted metrics and is bound by the reconstruction method's limitations, or reinforcement learning, which demands significant training efforts and often struggles with generalization. We anticipate that adopting a diffusion-based approach will surpass these constraints and lead to enhancements in the field. - Computer Vision
- Master Thesis
| Motivation: Create a realistic rendered benchmark to evaluate reinforcement agents, visual navigation tasks, interaction with other agents, navigation in scene with static and dynamic objects and humans.
How: Create a realistic rendered benchmark to evaluate reinforcement agents, visual navigation tasks, interaction with other agents, navigation in scene with static and dynamic objects and humans. - Artificial Intelligence and Signal and Image Processing
- Master Thesis
| Create an impactful tool for robotics research that can scale SLAM to city-scale.
- Intelligent Robotics
- Bachelor Thesis, Master Thesis, Semester Project
| Motivation: Building "dynamic Scene Graphs" that allow to add to the already acquired static information of the
scene data that can be learned from observations based on the users interactions
How: 'Mine' the knowledge from egocentric observations (e.g. aria glasses, HoloLens). Potentially, action
recognition, and tracking, etc. Will be helpful to process these observations. Then build a static scene graph with the information of the environment. Some information is stored explicitly but all the information should be ‘queryable by language’ such that we can answer - Artificial Intelligence and Signal and Image Processing
- Master Thesis
| Motivation:Use action recognition and object detection to extend the content of static scene graphs for a better
scene understanding
How: The static generated scene graph will be updated with information gathered from action
recognition networks and object detection algorithms, providing a better understanding of the scene - Artificial Intelligence and Signal and Image Processing
- Master Thesis
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