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👋 Hola! Hello! Hallo!
I am a PhD candidate at Matthias Nießner’s Visual Computing Group, at the Technical University of Munich.
I’m interested in computer vision, deep learning and optimization. My current research interests are focused on virtual avatars, generative models and 3D scene representations.
Before joining the group, I received a Master’s Degree in Computer Science from the Technical University of Munich and a Bachelor’s Degree in Computer Science from the Polytechnic University of Catalonia.
Experience
- Fellowship awarded to outstanding Master students to allow them developing state-of-the-art models. See page.
- See project’s page.
- Built a high-performance GPU cluster for the Deep Learning laboratory.
- Built a frontend with Vue.js and a backend for the cluster’s users.
- Designed and built a cluster for the BE-OP-LHC team at CERN using Kubernetes.
- Worked on a novel conversion of Binary Decision Trees to Conjunctive Normal Forms.
- See project’s page.
- Frontend and backend development.
Projects
In this project, I worked on the SLAM pipeline for an autonomous driving vehicle.
The tools I used for this project are, ROS, C++, PCL library, Ceres Solver, and Google Cartographer.
In addition, I created a ROS package that generates a cost map from a point cloud generated by SLAM. A cost map is a matrix where each cell contains a cost value. This value expresses how likely it is that the cell is occupied by an object. The cost value is also used to express “preferred” surfaces: for example, asphalt is preferred over grass.
In this project, we extended the work of Eisenberger, Zorah, Cremers, “Divergence-Free Shape Interpolation and Correspondence” 1. In their work, they present a method to calculate deformation fields between shapes embedded in $\mathbb{R}^D$. To do so, they compute a divergence-free deformation field represented in a coarse-to-fine basis using the Karhunen-Loéve expansion.
Tags
Contact
- marc.benedi@tum.de
- +49-89-289-18165
- 02.07.034 MI building - Garching TUM Campus
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Office Hours:
Tuesday 14:15 to 15:45 - Book an appointment
- @marcbenedi