LATIDIA · Robótica

Hacia un modelo de cimentación para nubes de puntos forestales

arXiv: 2609.24787v1Announce Type: cross Resumen: Los inventarios forestales dependen cada vez más de modelos de inteligencia artificial (IA) para derivar atributos forestales de nubes de puntos 3D a gran escala. Los modelos actuales suelen ser spe

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arXiv:2609.24787v1 Announce Type: cross Abstract: Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds. Current models are typically specialized to a single task, sensor, and forest type, making adaptation expensive in terms of annotations, computation, and expertise. We ask whether a single pretrained model can instead learn transferable representations across diverse forest inventory settings. Inspired by recent developments in language modelling and computer vision, we take a step toward a foundation model (FM) for 3D forestry. Using LitePT as backbone, we first establish a strong supervised baseline that sets a new state of the art on forest semantic and instance segmentation,