AI RESEARCH

Few-Click-Driven Interactive 3D Segmentation with Semantic Embedding

arXiv CS.CV

ArXi:2605.08925v1 Announce Type: new Interactive segmentation allows efficient label generation by leveraging user-provided clicks to progressively refine predictions, which is critical when fully supervised labels are costly or generalization to unseen classes is needed. Existing 3D interactive methods are limited: most operate sequentially, predicting only one object per iteration with binary masks, while several recent approaches depend on 2D foundation models and camera alignment to bridge the 2D-3D gap.