AI RESEARCH
Review and Evaluation of Point-Cloud based Leaf Surface Reconstruction Methods for Agricultural Applications
arXiv CS.CV
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ArXi:2604.03328v1 Announce Type: new Accurate reconstruction of leaf surfaces from 3D point cloud is essential for agricultural applications such as phenotyping. However, real-world plant data (i.e., irregular 3D point cloud) are often complex to reconstruct plant parts accurately. A wide range of surface reconstruction methods has been proposed, including parametric, triangulation-based, implicit, and learning based approaches, yet their relative performance for leaf surface reconstruction remains insufficiently understood.