Training data: None

Onboarding data:
Model-free: using static onboarding sequences to reconstruct 3DGS models, rendering templates for 2D detection (162 rendered images + 64 sampled static onboarding images). The average onboarding time for reconstructing a GS object and generating its templates/descriptors is about 105s.

Notes: For unified 3DGS reconstruction from pinhole and fisheye images, we use an adaptive perspective cropping strategy to preprocess static onboarding images. Then the object Gaussians are rapidly trained with these cropped pinhole images for 10k iterations. With the obtained GS models, we prepare templates as described above. For 2D detection, we use a modified CNOS augmented with appearance scores. The descriptor model is DINOv2, and the segmentor is SAM2.1. A postprocessing step is applied to fill small holes and remove small isolated areas.

Authors: Temporary Anonymity