mlsanityData to 14 Oct 2026

Generating real-time detailed ground visualisations from sparse aerial point clouds

arXiv 2507.18664 ↗First posted 24 Jul 2025cs.GR cs.CVcited by 0

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Abstract (arXiv)

Building realistic wide scale outdoor 3D content with sufficient visual quality to observe at walking eye level or from driven vehicles is often carried out by large teams of artists skilled in modelling, texturing, material shading and lighting, which typically leads to both prohibitive costs and reduced accuracy honoring the variety of real world ground truth landscapes. In our proposed method, we define a process to automatically amplify real-world scanned data and render real-time in animated 3D to explore at close range with high quality for training, simulation, video game and visualisation applications.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 2 references that are in the map. First posted on arXiv 24 Jul 2025.

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2 of 2 references.

References · 2

  1. 2021GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worldscited by 98
  2. 2020DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentationcited by 66

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