#label-free-learning News & Analysis

FoundObj: Self-supervised Foundation Models as Rewards for Label-free 3D Object Segmentation

FoundObj introduces a self-supervised framework for 3D object segmentation in point clouds without manual scene-level annotations, using reinforcement learning guided by semantic and geometric reward modules from foundation models. The approach demonstrates strong performance across benchmarks and shows particular promise in zero-shot and long-tail scenarios, advancing label-free computer vision capabilities.