Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding

arXiv:2403.17010v1 Announce Type: cross
Abstract: Safety-critical 3D scene understanding tasks necessitate not only accurate but also confident predictions from 3D perception models. This study introduces Calib3D, a pioneering effort to benchmark and scrutinize the reliability of 3D scene understanding models from an uncertainty estimation viewpoint. We comprehensively evaluate 28 state-of-the-art models across 10 diverse 3D datasets, uncovering insightful phenomena that cope with both the aleatoric and epistemic uncertainties in 3D scene understanding. We discover that despite achieving impressive levels of …

abstract art arxiv benchmark cs.cv cs.lg cs.ro perception predictions reliability safety safety-critical state state-of-the-art models study tasks type uncertainty understanding