ShambhaviJoshi/Drone_based_3D_Reconstruction_of_Plants_AAAI26

Drone-based 3D Reconstruction of Plants in Field Conditions Using Neural Radiance Fields (NeRFs)

This repository contains resulting 3D point cloud reconstructions generated using Neural Radiance Fields (NeRFs) for field-grown plants. The point clouds are outputs from a comparative study evaluating different image acquisition modalities under real-world agricultural field conditions.

These outputs accompany the paper:

Drone-based 3D Reconstruction of Plants in Field Conditions using Neural Radiance Fields Accepted at the First International Workshop on AI in Agriculture (AgriAI), co-located with AAAI 2026.

Project website: https://idealab-isu.github.io/Drone-based-3D-Reconstruction-of-Plants-AAAI26/ ---

What is included

This repository contains final 3D point cloud outputs reconstructed from NeRF models for field-grown plants. These outputs were generated using imagery captured with drone, handheld, and 360° imaging systems and are provided for visualization and qualitative inspection.

More information on the data

• —The dataset includes two crop types: mungbean and soybean
• —All data was collected on August 22, 2025

File naming and sensing modalities

• —DroneOrbit_Mung_aug22.ply → Point cloud from drone-based imagery for mungbean

• —Mung_360_aug22.ply → Point cloud from 360° camera imagery for mungbean

• —Files starting with Video_M* → Handheld imagery reconstructions of individual mungbean plants
• —M indicates mungbean

• —Files starting with Video_S* → Handheld imagery reconstructions of individual soybean plants
• —S indicates soybean

🛰️ Data Collection

• —Drone-based RGB imagery
• —360-degree ground imagery
• —Real field environments with natural illumination
• —Multiple viewpoints to support NeRF-based reconstruction

📥 How to Download

Using Hugging Face

git clone https://huggingface.co/datasets/ShambhaviJoshi/Drone_based_3D_Reconstruction_of_Plants_AAAI26
cd Drone_based_3D_Reconstruction_of_Plants_AAAI26
git lfs pull