Map scene generation framework based on language models

The design of map scenes is significant in the virtual reality and various other domains, gradually emerging as a key area of research. However, conventional coding-dependent approaches still demand high levels of expertise from designers and are associated with substantial design costs. Thus, in this paper, we introduce a map scene design framework by leveraging language models to streamline the process for users engaged in the map scene design. Specifically, our approach relies solely on natural language text to manipulate the map engine and fine-tune smaller models within the mapping domain, thereby eliminating the need for users to undertake secondary development. We illustrate our framework has been tested in 3D map scene design, with results indicating strong accuracy and efficient drawing capabilities.

Authors

Institutions

Publication Details

Published
2025-07-11
DOI
https://doi.org/10.1109/cisat66811.2025.11181759
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Map scene generation framework based on language models

Ruichen Wang, Yu Xu
Geographic Information Systems Studies
article

Map scene generation framework based on language models

Ruichen Wang, Yu Xu
article en

Abstract

The design of map scenes is significant in the virtual reality and various other domains, gradually emerging as a key area of research. However, conventional coding-dependent approaches still demand high levels of expertise from designers and are associated with substantial design costs. Thus, in this paper, we introduce a map scene design framework by leveraging language models to streamline the process for users engaged in the map scene design. Specifically, our approach relies solely on natural language text to manipulate the map engine and fine-tune smaller models within the mapping domain, thereby eliminating the need for users to undertake secondary development. We illustrate our framework has been tested in 3D map scene design, with results indicating strong accuracy and efficient drawing capabilities.

Civil Aviation University of China (CN)
Openalex Percentile: Top 67%
Geographic Information Systems Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.