SOTAVerified

Semantic Neural Radiance Fields for Multi-Date Satellite Data

2025-02-24Code Available0· sign in to hype

Valentin Wagner, Sebastian Bullinger, Christoph Bodensteiner, Michael Arens

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

In this work we propose a satellite specific Neural Radiance Fields (NeRF) model capable to obtain a three-dimensional semantic representation (neural semantic field) of the scene. The model derives the output from a set of multi-date satellite images with corresponding pixel-wise semantic labels. We demonstrate the robustness of our approach and its capability to improve noisy input labels. We enhance the color prediction by utilizing the semantic information to address temporal image inconsistencies caused by non-stationary categories such as vehicles. To facilitate further research in this domain, we present a dataset comprising manually generated labels for popular multi-view satellite images. Our code and dataset are available at https://github.com/wagnva/semantic-nerf-for-satellite-data.

Tasks

Reproductions