A Dataset of Temporally Consistent Instance Annotations for 4D Plant Phenotyping.

Abstract excerpt

Spatio-temporal 4D plant phenotyping requires high-quality datasets with precise and temporally consistent annotations. However, such datasets are currently limited due to the substantial effort required for data acquisition and manual annotation. To address this limitation, we present Sugar4D, a publicly available 4D plant phenotyping dataset of sugar beet acquired using a terrestrial LiDAR scanner. The dataset...

Topics

• Phenotype
• Plant Leaves
• Beta vulgaris