Department of Computer ScienceAcronym | D-INFK | Homepage | http://www.inf.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Computer Science | Child organizations | |
Open OpportunitiesWe extend the lamar.ethz.ch benchmark to develop accurate SLAM methods that can co-register drones, legged robots, wheeled robots, smartphones, and mixed reality headsets based on visual SLAM. - Computer Vision, Intelligent Robotics
- Bachelor Thesis, Master Thesis, Semester Project
| What optimizations are necessary to make reflective PPG sensors reliably work on tissue with limited blood perfusion?
Note: Candidates should have experience in hardware design (analog circuits, embedded systems, and basic signal processing). - Electrical and Electronic Engineering, Information, Computing and Communication Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| Fast 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
| Latent diffusion models (LDMs) [1] have recently emerged as a powerful tool for high-quality image generation, offering superior scalability and training efficiency compared to pixel-space diffusion models. While the network architectures of LDMs have received significant attention, other design aspects of these models (for example the forward noise schedule and the autoencoder) remain underexplored. This project aims to enhance the characteristics of LDMs, e.g., quality and efficiency, by investigating various design elements of latent diffusion models.
- Information, Computing and Communication Sciences
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| 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
| Digital capture of human bodies is a rapidly growing research area in computer vision and computer graphics that puts scenarios such as life-like mixed-reality (MR) virtual-social interactions into reach. Therefore, we offer projects for modeling and capturing humans at the intersection of computer vision, computer graphics, and machine learning. - Computer Graphics, Computer Vision, Virtual Reality and Related Simulation
- Master Thesis, Semester Project
| 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
|
|