DreamSat-2.0: Towards a General Single-View Asteroid 3D Reconstruction

Diaz, Santiago, Hu, Xinghui, Uwumukiza, Josiane, Lavezzi, Giovanni, Rodriguez-Fernandez, Victor, Linares, Richard

arXiv.org Artificial Intelligence 

To enhance asteroid exploration and autonomous spacecraft navigation, we introduce DreamSat-2.0, a pipeline that benchmarks three state-of-the-art 3D reconstruction models-Hunyuan-3D, Trellis-3D, and Ouroboros-3D-on custom spacecraft and asteroid datasets. Our systematic analysis, using 2D perceptual (image quality) and 3D geometric (shape accuracy) metrics, reveals that model performance is domain-dependent. While models produce higher-quality images of complex spacecraft, they achieve better geometric reconstructions for the simpler forms of asteroids. New benchmarks are established, with Hunyuan-3D achieving top perceptual scores on spacecraft but its best geometric accuracy on asteroids, marking a significant advance over our prior work.

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