SOURCE-LINKED INTELLIGENCE

Zero-Shot 3D Plant Organ Segmentation with SAM3 and Semantic NeRFs

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Accurate 3D plant organ segmentation is fundamental to automated phenotyping. Existing approaches rely on annotated training data or species-specific model configurations. We present an annotation-free pipeline for 3D plant organ segmentation, combining text-prompted SAM3 segmentation with semantic neural radiance fields (NeRFs). Given only multi-view RGB images and a list of class names, our zero-shot pipeline produces semantically labeled 3D point clouds without manual annotation, per-species fine-tuning, or domain-specific preprocessing. Multi-view NeRF fusion acts as effective implicit con

Read original source ↗ Open in workspace

recordType

paper

region

Global