A Semantic Segmentation System for generating context-based tile-maps

  • Leandro Gabriel UFF
  • Esteban Walter Clua UFF

Resumo


Training a Generative Adversarial Network (GAN) involves a two-step process: training the generator network and training the discriminator network. The generator tries to generate realistic data, while the discriminator aims to distinguish between real and generated data. In this work we propose a semantic segmentation system that uses regular images for generating semantic maps through Tensor Flow framework. These maps are associated with a discrete set of tiles, which can be used for training generation of game style tile-maps. Besides the data-set creation, our solution also allows the creation of tile-maps based on image samples.
Palavras-chave: classification, datasets generation, mobilenets
Publicado
06/11/2023
GABRIEL, Leandro; CLUA, Esteban Walter. A Semantic Segmentation System for generating context-based tile-maps. In: SIMPÓSIO BRASILEIRO DE JOGOS E ENTRETENIMENTO DIGITAL (SBGAMES), 22. , 2023, Rio Grande/RS. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 124–133.