Temporal latent fusion for sequential 3D shape completion in on-plant Korean melon growth monitoring

Abstract

Abstract has not been obtained from indexed metadata or an accessible article page.

Plant phenotyping relevance

オンプラントのメロン生育モニタリングにおける時系列3D形状補完手法が題名上の中心であり、植物形態の取得・推定に直接関係する。

Code and data availability

The paper describes a paper-specific dataset (2,513 RGB-D frames of 210 Korean melons with ground-truth meshes and caliper references) and states that code, trained weights, and data are publicly available, but no concrete repository URL or identifier is provided in the supplied blocks, so the assets cannot be directly

No evidence-backed public reproduction asset is currently recorded.