Projects
Some of my favourite projects I worked on. More games can be found on my Itch.io page and other projects are posted on
my github page.
Cyberbowl
Cyberbowl is a local multiplayer game, where the players compete in teams to win a football game.
Every character has special abilities that either help to score a goal or to prevent the other team from scoring.
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My role
This project was the graduation project for my Bachelor studies at the University of Applied Sciences Salzburg. It was developed in Unreal 4 by a total of 3 programmers and 7 artists. In this team my primary role was Gameplay development, where I took on tasks as needed and therefore was involved in everything from character movement, over gameplay management, like keeping track of time and score, to UI implementations.
Trailer
Trash Patrol
Trash Patrol is a couch-coop multiplayer game, where the players control cute raccoon characters and have to work together to steal items from a house.
In order to do so, the items have to be washed and cleaned before they can be handed into a trashcan. Simultaneously, the pack has to avoid the owner of
the house, who is not too happy that a bunch of raccoons is trying to steal his possessions.
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My role
This project was the graduation project for my Master studies at the University of Applied Sciences Salzburg. It was developed in Unreal 4 by a total of 2 programmers and 5 artists. In this team my primary role was AI development, which involved implementing the human occupant of the house. I was also responsible to incoperate the sound provided by our sound designer. Furthermore, I helped out as needed with several coding tasks as well as developed various parts of the prototype to test several mechanics before the actual development process started. Since the important game design alterations where decided by the whole team, I also took part in the design process, which however was not my main resposibility.
Trailer
Sketch to 3d-Model
Sketch to 3d-Model is a project with the goal of transforming a 2d input sketch to a 3d model. This is done using Deep Learning as well as Differentiable Rendering,
which are the basic building block of the resulting pipeline. The outputs of the pipeline are evaluated in a comparison with a state-of-the-art model as well as an ablation study. These results are briefly summarized and presented alongside the code in the project’s Github repository.
My role
This pipeline was the research project for my Master’s Thesis, which I implemented in the last 6 months of my Master’s studies. In addition to research, coding and evaluation, I also created and used a custom-made dataset using data from existing datasets. The creation for the used datasets is also described in the Github repository. Since this was also my first time working with Deep Learning and Differentiable Rendering, this learning process required extra effort and time, however, I learned a lot of new skills along the way.