Virtual Environment Generation with Artificial Intelligence - Mesquita, Paulo Abner; Rocha, Leonardo (Anais do Simpósio de Realidade Virtual e Aumentada (SVR); 2025: Anais do XXVII Simpósio de Realidade Virtual e Aumentada, 2025)
The creation of immersive 360° Virtual Reality (VR) environments remains a significant bottleneck. This pilot study explores leveraging generative artificial intelligence to create panoramic VR environments, represented as cubemaps, directly from textual descriptions. Inspired by recent text-to-3D methodologies but adapted for panoramic output, we propose a framework utilizing pre-trained text-to-image diffusion models, specifically Stable Diffusion for creative inpainting/generation, potentially combined with monocular depth estimation for consistency. The goal is to generate the six faces of a cubemap representing a coherent, 360° view suitable for VR applications, emphasizing the creative potential of generating unique environments from simple text prompts. This paper outlines the adapted methodology, discusses the advantages of cubemaps, compares them to other projection techniques (spherical, equirectangular), and highlights the potential for democratizing VR panorama creation for artists and other creative professionals looking for a tool that can leverage the creativity for computing.