Master's Thesis: Creation of synthetic vector maps through the use of Generative AI
Generative Adversarial Networks (GANs) and Latent Diffusion Models (LDMs) have shown huge potential in creating unique imagery based on reference content and other kinds of user guidance. This project seeks to research how these kinds of models can learn to produce synthetic vector maps representing the high-level structures and inherent rules that define the primary infrastructure elements in urban and suburban regions. Additionally, the use of simple text prompts is to be explored as a means of guiding the characteristics of the generated maps.
- Department
- ML Development
- Locations
- Göteborg
- Remote status
- Hybrid
Colleagues
Göteborg
What we value.
We’re all about collaboration. That’s because we’re solving a puzzle that cannot be completed alone. It takes trust, courage, creativity and transparency to deliver on our promise. Our team buys into this, so our customers buy into it. It’s just our way of staying on the same page.
About Repli5
We enable the development of autonomous vehicles with synthetic data. Our software reduces the cost and time required to train autonomous vehicles.
Master's Thesis: Creation of synthetic vector maps through the use of Generative AI
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