Crossmodal Few-shot 3D Point Cloud Semantic Segmentation via View Synthesis

This paper introduces a cross-modal few-shot approach for 3D point cloud segmentation, using multi-view synthesis with color and depth inpainting to address occlusions and reduce reliance on 3D annotations. A Co-embedding Network aligns features between synthesized views and original 3D data, while a weighted prototype network enhances segmentation performance.