1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2025★ 1 cited
From Canopy to Ground via ForestGen3D: Learning Cross-Domain Generation of 3D Forest Structure from Aerial-to-Terrestrial LiDAR
Juan Castorena, E. Louise Loudermilk, Scott Pokswinski +1
The 3D structure of living and non-living components in ecosystems plays a critical role in determining ecological processes and feedbacks from both natural and human-driven distur…
cs.CV2024
Learning Neural Radiance Fields of Forest Structure for Scalable and Fine Monitoring
Juan Castorena
This work leverages neural radiance fields and remote sensing for forestry applications. Here, we show neural radiance fields offer a wide range of possibilities to improve upon ex…
cs.LG2023
Representation Disentaglement via Regularization by Causal Identification
Juan Castorena
In this work, we propose the use of a causal collider structured model to describe the underlying data generative process assumptions in disentangled representation learning. This…